Executive Summary

Tamimi Markets, one of Saudi Arabia's largest and longest-established grocery retailers, faced a familiar enterprise problem at an unfamiliar scale: hundreds of millions of operational data points locked behind BI queues and specialist teams, while high-volume retail work, ordering, forecasting, customer engagement — stayed manual and spreadsheet-bound. Rather than pursue a narrow point solution, Tamimi partnered with NorthBay Solutions, an AWS Premier and Anthropic partner, to build AskBaba: a bilingual (Arabic/English) agentic AI platform powered by Anthropic's Claude on Amazon Bedrock, running inside Tamimi's own AWS environment and delivered where employees already work, in Microsoft Teams.

The result is a business milestone as much as a technical one: Tamimi Markets is the first retailer in the Kingdom of Saudi Arabia to run agentic AI at enterprise scale, not a pilot, not a single chatbot, but a governed, production platform of 19+ specialized Claude-powered agents that answer questions in seconds, automate daily purchase ordering, forecast demand, and re-engage customers. AskBaba delivers measurable value across every persona in the organization — store managers, category buyers, HR, IT, finance, and executive leadership and across every operational stream, from analytics and procurement to forecasting and customer engagement, all while keeping enterprise data under Tamimi's own governance. Claude powers both what AskBaba does for the business and how NorthBay designed, built, and delivered it.

Results at a Glance

Note: figures reflect observed production usage; select figures are being validated with Tamimi Markets during Anthropic's reference and consent process.

The Challenge

Tamimi Markets runs a nationwide network of stores generating enormous operational data, hundreds of millions of transaction line items across sales, inventory, stock movement, promotions, and procurement, flowing from SAP S/4HANA into an Amazon Redshift data warehouse of more than 130 tables. The data existed; access to it did not.

Store managers, category buyers, and executives depended on BI dashboards and analyst queues for even routine questions, how a store performed yesterday, which products were running low, whether a promotion moved volume. Answers took hours or days, arrived in English only, and required desk access. Meanwhile, high-volume operational processes such as demand forecasting, competitor price tracking, and customer win-back campaigns were manual, spreadsheet-driven, and dependent on a small group of specialists. Daily purchase-order creation, by contrast, already ran on TIPS, Tamimi’s own proven ordering platform, and one of the retailer’s strongest existing systems with room to add a real-time validation layer as volume and complexity grew.

Tamimi Markets wanted a single, trustworthy assistant its employees could talk to: one that understood retail language in both Arabic and English, answered from governed enterprise data rather than guesswork, respected each employee's role and permissions, and could safely take action, not just report. It had to serve every persona in the business, from the store floor to the boardroom, run inside the tools employees already use (Microsoft Teams), and scale from a pilot to the entire organization.

The Solution: An Agentic Platform Built on Claude & AWS

NorthBay Solutions designed AskBaba as an agentic AI platform with Claude at its core, running on Amazon Bedrock inside Tamimi Markets' own AWS environment, keeping the client's enterprise data under the customer's governance, so every persona gets a different, role-appropriate answer from the same trusted foundation.

A supervisor–specialist agent architecture

Rather than a single monolithic bot, NorthBay built a LangGraph (Day 1 Architecture and progressing towards an AgentCore architecture) multi-agent system in which a Claude-powered supervisor understands each request, then routes it to one of 19+ specialist agents, sales analytics, inventory, stock movement, sales budgets, product catalog, competitor pricing, predictive forecasting, purchase-order creation and inquiry, HR knowledge, IT incidents, business events, weather, scheduled reporting, and more. Each specialist combines Claude's reasoning with governed tools: text-to-SQL over the Redshift warehouse, retrieval-augmented generation (RAG) over HR and policy documents, ServiceNow ticketing, SAP purchase-order APIs, and Airflow job scheduling. Agents complete their task or escalate back to the supervisor, so conversations flow naturally across domains.

Why Claude

Reasoning over enterprise schemas. Claude reliably translates ambiguous, bilingual retail questions into precise SQL over a 130+ table warehouse, respecting business rules (posting vs. transaction dates, fresh vs. non-fresh classification, store hierarchies).

• Multimodal understanding. Claude's vision capability reads product photos, shelf images, and competitor brochures; voice queries flow through transcription into the same agents.
• Arabic + English fluency. One assistant serves the whole workforce, detecting and responding in each user's language.
• Safety and control. Amazon Bedrock Guardrails, role-based access control enforced at the agent layer, and prompt-injection hardening keep responses grounded and appropriate for the workplace.
• The Solution: An Agentic Platform Built on Claude & AWS

Built and delivered with Claude

The platform is built on AWS with infrastructure-as-code (Terraform), CI/CD with environment promotion and production deploy authorization, SageMaker ML pipelines for demand forecasting with SHAP explainability, and event-driven integration (SQS, Lambda, Airflow) to SAP and messaging channels. NorthBay's delivery team also adopted Claude in its own engineering workflow, using Claude-assisted development with mandatory human review, plan-first tickets, and self-review gates. In effect, Claude powers both what AskBaba does for Tamimi Markets and how NorthBay built and delivered it, accelerating architecture, coding, and testing from the first release through every extension phase, shortening time-to-production without compromising the engineering rigor an enterprise platform demands.

Delivery & Adoption

AskBaba is in production and has been serving Tamimi Markets employees since 2025, delivered through four major releases and two funded extension phases, evidence of sustained customer commitment rather than a one-off pilot.

• Production platform. Live across development, QA, and production environments on AWS, with formal release management, a 12-week software-quality-assurance cycle, and a hotfix-governed production freeze discipline.
• Where employees work. Delivered inside Microsoft Teams (with an embedded web chat option), so adoption required no new application, employees message AskBaba like a colleague.
• Broad functional adoption. Natural-language sales/inventory/procurement analytics; HR-policy Q&A via RAG; ServiceNow incident creation from chat; a real-time validation layer on daily TIPS purchase-order creation, with SAP integration; ML demand forecasts with explainable drivers; image, barcode, and voice inputs; and administrator-composed broadcast messaging.
• Operational governance. Enterprise security program (IAM least-privilege, KMS encryption, secrets management, OIDC-only pipelines), PDPL-aligned data handling, and full auditability of agent actions.

Business Impact

AskBaba has changed the day-to-day economics of data access and retail operations at Tamimi Markets:

• From days to seconds. Routine analytics questions that previously waited on BI/reporting queues are now answered in under 30 seconds, self-service, 24/7, in Arabic or English.
• Growing daily usage. Adoption grew more than 40% within months of launch (from ~100 to 140+ daily active employees) across stores and head office.
• Half a billion+ records at conversational reach. The assistant reasons over 500M+ transaction line items and 130+ warehouse tables previously accessible only to data specialists.
• TIPS, validated. AskBaba adds a real-time validation layer on top of TIPS, Tamimi’s proven purchase-order platform, cross-checking daily purchase-order creation across the store network and giving every PO an explainable rationale freeing buyer hours for higher-value work.
• Forecasting with accountability. SageMaker demand forecasts with SHAP explainability inform ordering decisions, with drivers (events such as Ramadan and Eid, weather, promotions) visible to the business.
• Faster employee communications. Administrators broadcast rich announcements to 1,000+ recipients across Teams and web chat in minutes, with per-recipient delivery tracking.

Value Across Business

AskBaba's supervisor-agent architecture means the same platform serves every persona in the business differently — each getting the analytics, automation, or knowledge relevant to their role, without separate tools or integrations to manage.

What's Next?

Tamimi Markets and NorthBay Solutions continue to extend the platform on the same Claude-on-Bedrock foundation: competitor price intelligence across major KSA retailers, and personalized customer re-engagement identifying dormant customers and lapsed products, matching them to live promotions, and reaching them over WhatsApp and email with consent-managed, bilingual campaigns. Each increment reuses the same governed agent architecture, shortening time-to-value with every release and extending Tamimi's first-mover position as Saudi retail's digital transformation, aligned with Vision 2030, accelerates.

About NorthBay Solutions

NorthBay Solutions is an AWS Premier consulting partner and Anthropic partner specializing in data, analytics, and generative AI. NorthBay designs and delivers production AI systems, from agentic assistants to ML platforms, for enterprises across the Middle East, North America, and beyond.

Tamimi Markets is one of Saudi Arabia’s largest grocery retail chains, operating a nationwide network of stores and serving millions of customers with a commitment to quality and value. It is the first retailer in the Kingdom to run agentic AI at enterprise scale, built end to end on Anthropic’s Claude, extending value across every persona in the business, from store operations to executive leadership.

Availability

AskBaba was designed and delivered by NorthBay Solutions on Anthropic's Claude via Amazon Bedrock. To learn how NorthBay can bring production-grade Agentic AI to your enterprise, connect with an expert or find offerings on the AWS Marketplace.

Meet Our Customer

Solution

NorthBay’s technology team supporting Grow Credit established Snowflake as the central analytical data layer.

Operational data is replicated into Snowflake, creating a dedicated analytical environment separate from customer-facing transaction processing. This gives Grow Credit a reusable foundation for reporting, analysis, and downstream workflows while reducing the need to run analytical workloads directly against production systems.

Snowflake also provides a common data layer for multiple internal and external use cases. Internal teams can use centralized data for reporting and analytics, while downstream workflows and approved partner requirements can be supported without creating separate point-to-point connections to production systems.

Role-based access and purpose-specific Snowflake environments help govern how data is accessed across different workloads, supporting controlled use of data within Grow Credit’s regulated operating environment.

The Outcome

Snowflake has given Grow Credit more than a traditional data warehouse.

The platform provides a reusable, governed data layer between operational systems and the teams, workflows, and partners that require analytical data.

This enables Grow Credit to:

• Separate analytical workloads from customer-facing transaction processing.
• Support reporting and analytics from a common data foundation.
• Reduce the need for individual integrations directly against production systems.
• Support controlled internal and external data-consumption requirements.
• Scale new analytical and data-engineering use cases from a shared foundation.

The result is a simpler and more scalable data architecture in which production systems remain focused on customer operations while Snowflake provides the centralized foundation for reporting, analytics, integrations, and controlled data sharing.

Why NorthBay?

NorthBay Solutions is an AWS Premier Consulting Partner and Snowflake AI Data Cloud Select Services Partner. With Snowflake, NorthBay helps organizations retire legacy, on-premises data warehouses and modernize onto a unified data platform running on AWS.

NorthBay's Snowflake practice spans data warehouse and data lake migration, data engineering and ETL/ELT modernization, BI and reporting, master data management, and real-time streaming, with generative AI enablement via Snowflake Cortex as an emerging capability.

Backed by 10+ years of AWS delivery experience and Snowflake platform expertise, NorthBay gives Snowflake customers a single, security-first partner to plan, migrate, and operate data and AI workloads on AWS.

Learn more at northbaysolutions.com/partners/snowflake.

Meet Our Customer

Our customer is one of Saudi Arabia's largest and longest-established grocery retail chains, operating a nationwide network of stores and serving millions of customers across the Kingdom.

As the business grew, so did its data. Every day its stores generate an enormous volume of operational detail — sales, inventory, stock movement, promotions and procurement — flowing from SAP S/4HANA into an Amazon Redshift data warehouse that now holds more than 600 million transaction line items and 125 million baskets, growing by over half a million line items each day. The company had built a genuine enterprise data asset. What it wanted next was to put that asset directly into the hands of the people running the business, in the language they think in, at the moment they need it.

The Challenge

The data existed. Access to it did not.

Store managers, category buyers and executives depended on BI dashboards and analyst queues for even routine questions — how a store performed yesterday, which products were running low, whether a promotion moved volume. Answers took hours or days, arrived in English only, and required desk access. A store manager and a member of the executive team waited in the same report queue.

At the same time, the highest-volume operational processes remained manual. Daily purchase-order creation for fresh and non-fresh goods, demand forecasting, competitor price tracking and customer win-back campaigns were spreadsheet-driven and dependent on a small group of specialists — work that consumed skilled hours without scaling.

The customer set NorthBay a deliberately demanding brief: a single, trustworthy assistant that employees could simply talk to. It had to understand retail language in both Arabic and English, answer from governed enterprise data rather than guesswork, respect each employee's role and permissions, and safely take action — not just report on it. It had to serve every persona in the business, from the store floor to the boardroom, run inside the tools employees already use, and scale from a first release to the entire organisation.

The Vision

NorthBay designed an agentic AI platform running on Amazon Bedrock inside the customer's own AWS environment, so enterprise data stays under the customer's governance and every persona receives a different, role-appropriate answer from the same trusted foundation.

A supervisor-and-specialist agent architecture

Rather than a single monolithic bot, NorthBay built a multi-agent system on Amazon ECS Fargate in which a supervisor agent interprets each request and routes it to one of nineteen specialists — sales analytics, inventory, stock movement, sales budgets, product catalogue, competitor pricing, predictive forecasting, purchase-order creation and inquiry, HR knowledge, IT incidents, business events, weather and scheduled reporting among them. Each specialist pairs model reasoning with governed tools: text-to-SQL over the Redshift warehouse, retrieval-augmented generation over HR and policy documents on Amazon Aurora Serverless v2 with pgvector, ServiceNow ticketing, SAP purchase-order APIs, and Airflow job scheduling on Amazon MWAA. Agents either complete their task or escalate back to the supervisor, so a conversation can move across domains without the employee needing to know which system holds the answer.

Reasoning that holds up against a real enterprise schema

The hard part of retail analytics is not generating SQL — it is generating correct SQL against a warehouse that encodes years of business rules. Anthropic's Claude models on Amazon Bedrock translate ambiguous, bilingual retail questions into precise queries across 130+ tables, respecting posting versus transaction dates, fresh versus non-fresh classification and store hierarchies. Vision capability reads product photos, shelf images and competitor brochures; voice queries flow through Amazon Transcribe into the same agents. One assistant detects and responds in each user's language, so Arabic and English speakers share a single platform rather than two.

Governed by design

Amazon Bedrock Guardrails, role-based access control enforced at the agent layer and prompt-injection hardening keep responses grounded and workplace-appropriate. The platform is deployed with infrastructure-as-code, CI/CD with environment promotion and explicit production-deploy authorisation, Amazon SageMaker AI pipelines for demand forecasting with SHAP explainability, and event-driven integration to SAP and messaging channels. Security follows an enterprise programme of IAM least-privilege, KMS encryption, managed secrets and OIDC-only pipelines, with PDPL-aligned data handling and full auditability of agent actions.

Outcome

The platform has been in production since 2025, delivered through four major releases and two funded extension phases, with a third in planning — sustained commitment rather than a one-off pilot. It runs across development, QA and production environments with formal release management, a 12-week software-quality-assurance cycle and hotfix-governed production freeze discipline. It is delivered inside Microsoft Teams, with an embedded web chat option, so adoption required no new application: employees message the assistant like a colleague.

The change is as much economic as technical:

• Self-service analytics. Questions that previously entered a reporting queue are answered conversationally, removing a dependency that constrained decisions at the point of operation.
• Procurement automation. Purchase orders are created automatically every morning at 08:30 KSA, integrated end to end with SAP, replacing a manual spreadsheet process and returning buyer hours to negotiation and assortment strategy.
• Forecasting with accountability. SageMaker demand forecasts with SHAP explainability inform ordering, with drivers — events such as Ramadan and Eid, weather, promotions — visible to the business rather than buried in a model.
• Enterprise data at conversational reach. Records that were the preserve of data specialists are now open to any authorised employee, under the same governance.
• Measurable internal communication. Organisation-wide announcements carry per-recipient delivery tracking, on a pipeline validated at 1,000+ recipients.

Value across the business

Because the supervisor-agent architecture separates routing from expertise, the same platform serves each function differently — without separate tools or integrations to manage. Six of seven functions are live in production today.

AWS Services

The project heavily utilized AWS services to ensure scalability and efficiency:

Why NorthBay?

From the outset this was built for daily operational use across an entire workforce — which meant release management, security review, bilingual quality assurance, and the discipline to ship one use case, prove it in production, and expand from there. NorthBay is an AWS Premier Consulting Partner with an AI Consulting Services Competency and deep delivery experience in the region, and applied the same engineering rigour to an agentic system that it would to any enterprise platform: governed data access, explainable automation, and a production operating model from the first release.

Meet Our Customer

IBL Mauritius is a diversified conglomerate based in Mauritius, boasting a rich history of over 190 years. The group operates across nine business clusters, encompassing more than 280 brands in sectors such as agro-industry, building and engineering, commercial, financial services, hospitality, life sciences, logistics, manufacturing and processing, and property. Its agro operations offer sugar cane growing, milling and refining in Mauritius and the East African region. With a presence in 22 countries worldwide, IBL employs approximately 37,950 team members, making it one of Mauritius' largest employers. The group's strategic objective is to be recognized as a leading international entity, anchored in a robust investment portfolio, a culture of excellence, and world-class expertise.

The Challenge

When IBL engaged NorthBay Solutions, it was for a very specific reason: they were seeking an experienced partner to guide them on their data center migration from on-premises to AWS Cloud. Few of their challenges were addressed during this migration.

1. Transferring large volumes of data from on-premises systems to AWS while ensuring data integrity and minimal downtime.
2. Ensuring consistent user access across environments.
3. Implementing and managing multi-factor authentication (MFA) for user authentication.
4. Configuring a DR site in a different AWS account for ensuring seamless failover processes.
5. Ensuring that multi-account setups and the use of AWS Control Tower align with best practices and prevent mismanagement.
6. Maintaining centralized logging, auditing, and compliance reporting across multiple AWS accounts.

The Implication

Transitioning to the new environment brings several operational and strategic considerations. The following key implications were taken into account:

1. Increased administrative tasks during the migration phase, including account setup, backup configurations, and user access management.
2. Potential for service disruption if the migration and cutover are not carefully planned.
3. Higher initial costs due to resource provisioning and data transfer fees.
4. Staff need to familiarize themselves with AWS services, such as Elastic Disaster Recovery, FSx
5. Dependence on AWS's uptime and support infrastructure for critical business operations.

Solution

Following are the highlights of the solution provided to IBL which were based upon AWS best practices of architecture design, high availability, security and performance.

1. Used AWS Organizations and Control Tower for account provisioning and centralized governance.
2. Implemented identity and access management.
3. Configured MFA on accounts to enhance security.
4. Utilized AWS DataSync and Elastic Disaster Recovery to facilitate seamless data and application migration.
5. Configured Site to Site VPN between on premises to Production Site and DR Site.
6. Deployed DR systems using EDR for EC2, DataSync for FSX and also S3 bucket synchronization to ensure availability during disaster.
7. Implemented centralized logging and security tools like AWS Security Hub, GuardDuty, and CloudTrail.

AWS Services

The project heavily utilized AWS services to ensure scalability and efficiency:

Benefits

Below are some of the prominent benefits of the AWS solution provided to IBL.

1. Easily scale resources to meet business demands without investing in additional hardware
2. AWS's built-in security services, centralized access control, and MFA for better protection
3. Higher resilience with geographically distributed DR site and automated recovery tools
4. Simplified management of resources and users across multiple accounts with AWS Control Tower and SSO
5. Centralized audit and logging services ensure compliance with regulatory requirements

As a result of IBL's partnership with NorthBay Solutions, they have moved their critical business applications to AWS and also established a DR Site for Business Continuity.

NorthBay is now providing Managed Support Services (MSP) to the IBL and looking after all of their AWS infrastructure’s operations, security and maintenance.

Meet Our Customer

The Scientific and Technological Research Council of Türkiye (TÜBİTAK) is Turkey's leading agency for advancing science, technology, and innovation. Established in 1963, TÜBİTAK's mission is to promote, manage, and fund scientific research while shaping Turkey's national R&D agenda. An autonomous organization, TÜBİTAK is governed by a Scientific Board composed of distinguished scholars from universities, industry, and research institutions. It plays a pivotal role in fostering a science-driven culture and supporting the country's technological growth.

Vision

TÜBİTAK's ultimate goal is to create a Turkish-first LLM that can serve as a foundation model for a variety of downstream applications. This model would empower future AI initiatives in Türkiye and provide an essential tool for further fine-tuning across different sectors.

Solution

Our collaboration with TÜBİTAK involved a comprehensive approach to building their LLM using AWS infrastructure:

• Tokenizer Training: We developed new tokenizers optimized for Turkish, using a large, curated Turkish NLP dataset.
• Tokenizer Evaluation: We assessed tokenizers through fertility scores and made iterative improvements to enhance efficiency.
• Data Preparation & Sharding: TÜBİTAK’s data was preprocessed, tokenized, and sharded to maintain quality and maximize training performance.
• AWS Pre-Training Code: Leveraging Fully Sharded Data Parallel (FSDP) techniques, we developed and validated pre-training code on AWS for optimized scaling.
• Data Experiments: We ran experiments incorporating cultural data to improve model performance and generated insights based on results.
• Full Pretraining: The LLM was pre-trained with a 5% English data mix, allowing for benchmarking against both Turkish and international standards.
• Fine-Tuning: After pretraining, the LLM underwent multiple fine-tuning cycles to improve performance on the Turkish Leaderboard Dataset.
• Model Merging: We experimented with merging models and conducted performance assessments to measure improvement over baseline results.
• Comprehensive Evaluation: Metrics were captured throughout the process, enabling comparative analysis and identification of the most effective development strategies.

AWS Services

The project heavily utilized AWS services to ensure scalability and efficiency:

Benefits

TÜBİTAK achieved significant milestones through this initiative:

10x Faster Training: AWS P5 instances dramatically reduced training time, enabling rapid iteration and experimentation.

Turkish LLM Leaderboard Success: The fine-tuned model is now challenging the top-performing models on the Turkish LLM Leaderboard, marking a major leap in Turkish NLP capabilities.

Next Steps

TÜBİTAK is continuing its work to refine and fine-tune the LLM, with a vision to create an even more sophisticated Turkish-language model that will push the boundaries of AI and NLP in Türkiye.

Meet Our Customer

Founded in 2015, Getir is a trailblazer in ultra-fast delivery services, offering groceries and restaurant meals on-demand through its intuitive mobile app. As a leader in the convenience economy, Getir rapidly scaled its operations, expanding both its customer base and geographic reach.

Vision

Getir envisioned a customer support experience transformed by AI-driven technology. Their goal was to reduce the burden on human agents by using advanced bots that could automatically summarize chat conversations and generate assistive scripts, empowering agents to deliver faster, more accurate responses while maintaining high-quality support.

Solution

NorthBay developed and deployed a sophisticated AI-driven customer support solution tailored to meet Getir’s needs. The solution centered on a RAG-based chatbot system that leveraged advanced natural language processing and retrieval capabilities to:

• Improve operational efficiency by automating routine support tasks.
• Enhance customer satisfaction by reducing response times and offering more accurate solutions.
• Provide scalable, multi-lingual support to assist Getir’s expanding global customer base.

The chatbot not only assisted in customer interactions but also acted as a real-time support tool for agents, automatically summarizing chats and providing relevant information for complex cases. This allowed agents to handle more inquiries while maintaining high service quality.

AWS Services

The project heavily utilized AWS services to ensure scalability and efficiency:

Benefits

Improved customer service KPIs:

The AI-driven chatbot system helped Getir significantly improve key performance indicators such as first response time, resolution time, and customer feedback scores. By automating routine inquiries and offering faster responses, Getir was able to address customer needs more efficiently, leading to better overall service performance.

Elevated customer satisfaction:

With consistent and accurate support, customers experienced quicker resolutions and more personalized interactions, regardless of the language or complexity of the issue. This improved satisfaction, leading to higher retention rates and positive feedback.

Increased operational efficiency:

By streamlining support workflows, the AI-enhanced chatbot allowed support agents to focus on more complex cases. Automation reduced the time spent on repetitive tasks, enabling agents to handle higher volumes of tickets without compromising quality.

Reduced operational costs:

AI-assisted operations reduced the need for additional human resources in the customer support center. Automated responses, chat summarization, and agent assistance minimized the manual workload, lowering staffing costs and increasing overall cost efficiency.

Multi-language support:

The scalable, AI-powered system provided seamless support across multiple languages, enabling Getir to serve a diverse, global customer base without the need for a large, multi-lingual support team. This feature was vital as Getir expanded into new markets.

Next Steps

As part of an ongoing commitment to innovation, NorthBay will continue to collaborate with Getir to productionize additional enhancements to the chatbot system, ensuring it remains at the cutting edge of customer support technology.

Meet Our Customer

Riviana Foods Inc., America’s leading rice company, holds a distinguished position as the most extensive marketer of wild rice in the world. As a subsidiary of Ebro Foods, a global leader in the rice sector, Riviana benefits from the extensive expertise and resources of its parent company, which operates across over eighty countries in Europe, North America, Asia, and Africa. This global presence allows Riviana to offer a comprehensive selection of rice products, meeting diverse market demands through an expansive network of subsidiaries and brands. Riviana’s commitment to quality, innovation, and sustainability has positioned it as a trusted choice for consumers and a leader in the rice industry.

In addition to its diverse product portfolio, Riviana operates with a deep-rooted commitment to social responsibility. Through initiatives like “Jars of Hope,” in partnership with the California Association of Food Banks, and collaborations with Mercy Chefs to support vulnerable communities, Riviana is dedicated to giving back and making a positive impact. Riviana’s rice brands offer a range of options to meet various culinary needs, from nutritious meal solutions to quick and convenient options, making it easy for families to enjoy quality rice-based meals at home.

The Implication

Implementing an AI-enabled chatbot solution offers Riviana Foods a significant opportunity to enhance its customer support efficiency and deliver a more streamlined, responsive experience to its diverse audience. By automating responses to routine inquiries, the chatbot reduces the volume of inquiries requiring human intervention, allowing Riviana’s support agents to dedicate their efforts to more complex cases. This shift not only improves operational efficiency but also accelerates response times, ensuring a quicker and more satisfying experience for consumers, manufacturers, and retail partners.

Additionally, the solution’s integration with Riviana’s existing systems, such as Salesforce, provides a seamless escalation process for cases that require human attention, complete with conversation history and context. The chatbot’s built-in feedback mechanisms and knowledge base refinement also allow Riviana to evolve its support capabilities over time, aligning responses with evolving customer needs. By deploying this AI-driven system, Riviana Foods is positioned to scale its support operations in a cost-effective way, enhancing customer satisfaction and reinforcing its commitment to service excellence as the company continues to grow.

Solution

NorthBay Solutions, an AWS Premier Partner, crafted a comprehensive AI-enabled chatbot solution to transform Riviana Foods' customer support experience. This solution employs generative AI to deliver efficient, brand-specific responses, improving engagement and operational efficiency for Riviana's multiple brands. By integrating directly with Riviana’s existing workflows, the solution enhances response times and reduces agent workload, allowing customer support teams to focus on complex inquiries while routine questions are handled instantly by the chatbot. The chatbot’s branded interface offers users an intuitive experience, providing responses tailored to each brand’s unique tone and guidelines. For inquiries that require human assistance, the chatbot escalates with conversation history intact, streamlining the handoff to live agents.

The solution’s core components include:

1. User-Friendly Chatbot Interface: The chatbot interface allows users to submit questions in real time, branded in line with Riviana’s design standards and providing instant responses. It also includes escalation options triggered by keywords or rules defined by the Riviana team.
2. Admin Interface: The role based admin portal provides an intuitive platform for managing chatbot knowledge bases, users and roles, and chat feedback collection. Administrators can update knowledge base documents, manage access with role-based controls, and monitor conversation logs and telemetry data.
3. Knowledge Base Management and Feedback: The chatbot includes mechanisms for knowledge base updates, allowing periodic manual improvements based on customer feedback, which ensures ongoing enhancement of the chatbot’s responses.
4. Salesforce Integration: Integration with Salesforce enables seamless creation and management of support cases, allowing automated case generation, escalation, and tracking within Riviana’s support ecosystem.
5. Scalability and Monitoring: Built on AWS, the chatbot solution is scalable to handle varying volumes of inquiries, with application logs maintained in Amazon CloudWatch for performance monitoring and troubleshooting. Non-production environments are spun up as needed to optimize cost.

By leveraging AWS services such as Amazon Bedrock, ECS, CloudWatch, Amazon Aurora Serverless PostgreSQL and others, Riviana’s AI-enabled chatbot solution operates within a secure and scalable environment. This system significantly enhances customer engagement and operational efficiency, reducing manual support tasks, optimizing response times, and delivering a consistent, brand-aligned customer experience across all of Riviana’s brands.

AWS Services

The following is the list of core AWS Services used by Riviana:

Benefits

Implementing the AI-enabled chatbot solution provides Riviana Foods with several significant business benefits:

Enhanced Customer Support Experience: The generative AI-powered chatbot enhances the customer support experience by providing rapid and accurate responses to frequently asked questions. With instant assistance available around the clock, Riviana’s customers experience improved satisfaction, strengthening brand loyalty and engagement.

Operational Efficiency: Automating routine customer inquiries with the chatbot significantly reduces the manual effort required from support agents. This efficiency enables Riviana Foods to allocate resources strategically, allowing agents to focus on complex cases while maintaining a high quality of customer service.

Scalability: The solution’s ability to handle inquiries across multiple brands and channels makes it highly scalable. As Riviana Foods expands its customer base and product lines, the chatbot solution can easily be scaled to meet increasing demand without proportional increases in staffing.

Continuous Improvement: Feedback from customer interactions is collected and used to update the knowledge base periodically, ensuring that responses remain relevant and accurate. This iterative improvement cycle keeps the chatbot’s performance aligned with evolving customer needs and expectations.

Data-Driven Insights: The solution provides valuable insights into customer interactions, allowing Riviana Foods to refine support strategies, identify common issues, and improve product offerings. Leveraging these insights helps Riviana to make informed, data-driven decisions that enhance customer satisfaction and operational effectiveness.

Cost Savings: By automating a substantial portion of customer interactions, Riviana reduces the need for extensive human resources in its support operations. These cost savings can be redirected to other strategic initiatives, promoting growth and innovation.

Improved Brand Consistency: The chatbot ensures a consistent, brand-aligned experience across Riviana’s various brands, reinforcing a cohesive customer journey and strengthening brand identity.

By leveraging the power of AWS and the expertise of NorthBay Solutions, Riviana Foods has successfully implemented an AI-driven chatbot solution that elevates customer support, enhances operational efficiency, and provides actionable data-driven insights for ongoing optimization.

Meet Our Customer

Getir is a Turkish rapid delivery company that operates a mobile app-based grocery delivery service. Founded in 2015, Getir has expanded rapidly, offering customers the convenience of ordering groceries, snacks, and other everyday items through their app and having them delivered within minutes. It's gained popularity for its quick delivery times and wide range of available products. Getir has also initiated GetirMore, GetirFood, GetirWater, GetirLocals, GetirDrive, GetirJobs, GetirBiTaxi, and n11.

While users fulfill their instant needs in minutes with Getir, they get their weekly grocery shopping done on GetirMore. They get takeout from GetirFood, and keep in contact with their local shops through GetirLocals. They place orders for water on GetirWater, and use GetirBiTaxi or GetirDrive for transportation. Also find employees, services, or jobs they need with GetirJobs.

They continue to make their users' lives easier in all 81 provinces of Turkey, as well as in the USA and Europe.

The Implication

Through a comprehensive Discovery Phase, NorthBay team gathered the customer requirements and presented a solution based on AWS GenAI/ML services. This collaborative approach facilitated the development of a transparent and trusted solution design tailored for Getir's current and future requirements. NorthBay further solidified this foundation by crafting detailed solution diagrams and communication flow charts ensuring a solution that perfectly aligned with Getir's needs.

Solution

NorthBay Solutions, a Premier Tier AWS Partner, stepped in as the ideal collaborator. By leveraging their profound expertise in cloud architecture, specially GenAI, NorthBay crafted a comprehensive solution tailored to Getir’s specific needs.

Following services were provided:

API Integration: NBS has provided an Agent and Customer guidance API allowing Getir to integrate with existing CRM workflows. API accepts “summarized” customer chats that are tagged with “reason” and “vertical” in the form of an API request payload.

Customer and Agent Guidance: The request payload received from the API was used for the generation of an assistive script for support agents using the GenAI approach.

Prompt Engineering: NBS build guardrails within the AI system to identify and manage out-of-context or irrelevant queries, maintaining relevance and appropriateness in AI responses.

Admin Web Interface: NBS created a basic web interface where Getir staff can upload new agent training documents. This interface enables the team to manage documents for the duration of the POC.

Data Ingestion: NBS processed and vectorized relevant data sources, including agent training materials and structured data for output generation.

Leveraging the power of AWS, Getir successfully runs its Live Support Chatbot in a secure and scalable cloud environment.

Benefits

Implementing a Live Support GenAI based Customer and Agent guidance solution hosted on AWS could offer significant business benefits:

• 24/7 Support Availability: Getir aims to provide round-the-clock support to its customers, ensuring assistance is available whenever needed. By deploying GenAI solutions on AWS, the company can offer instant responses to customer queries, order updates, and assistance with common issues, regardless of the time of day or night. This availability enhances customer satisfaction and trust in Getir's service.
• Cost Savings: Prior to implementing GenAI solution, Getir experienced high operational costs associated with staffing a large customer support team to handle inquiries and issues. With a GenAI based solution hosted on AWS, the company can automate a significant portion of its support tasks, reducing the need for additional human resources. This results in substantial cost savings in terms of manpower, training, and overhead expenses.
• Scalability: Getir experiences fluctuating demand throughout the day, with peak times during evenings and weekends. By leveraging AWS's scalability features, GenAI solution can dynamically allocate resources to handle spikes in customer inquiries and order requests. This ensures that Getir maintains high service levels even during periods of increased activity, without the need for manual intervention.
• Improved Efficiency: GenAI capabilities enable it to quickly analyze and respond to customer queries, track orders, and provide personalized recommendations based on user preferences. This efficiency streamlines the customer support process, reducing resolution times and enhancing overall service quality. Customers receive prompt assistance, leading to higher satisfaction levels and repeat business.
• Data Insights: GenAI solution collects and analyzes vast amounts of data from customer interactions, including common inquiries, feedback, and purchasing patterns. RapidDelivery can leverage these insights to optimize its operations, improve service offerings, and identify areas for innovation. For example, analyzing frequently asked questions could inform updates to the mobile app interface or additions to the product catalog.
• Enhanced Customer Experience: By deploying GenAI solution, Getir enhances the overall customer experience by providing instant, personalized support directly within the mobile app. Customers can quickly resolve issues, track orders in real-time, and receive proactive updates on delivery status. This convenience and responsiveness build trust and loyalty among users, encouraging them to continue using RapidDelivery for their grocery needs.
• Competitive Advantage: Getir can gain a competitive edge in the crowded grocery delivery market by offering innovative and efficient customer support through GenAI Customer and Agent guidance system. The company sets itself apart from competitors by prioritizing customer convenience, reliability, and satisfaction. This differentiation attracts new customers and retains existing ones, driving growth and market share expansion.

About NorthBay

Northbay is a fast-growing, 100% AWS focused onshore/offshore AWS Premier Consulting Partner, supporting our customers to accelerate the reinvention of their applications and data for a cloud native world. Our >350 AWS certified employees excel in developing and deploying database & application migrations, data lakes and analytics, ML/AI, GenAI, DevOps and application and data modernization/development that drive measurable business impact.

We hold the following competencies, specializations and programs of AWS:

• Generative AI and Machine Learning

• Data & Analytics
• DevOps
• Mobile
• Education
• Migration Competency
• MSP Partner
• Public Sector Partner
• Database Ready
• Database Freedom
• Solution Provider Partner
• Well Architected

Meet Our Customer

Scoutek provides the power of total trail camera and photo management using the most advanced technology available and is designed to work for all Scoutek Certified cameras, and any wireless cameras that can transmit photos to a specified email address.

Scoutek trail cameras are designed for outdoor use, typically in wildlife monitoring, hunting, or environmental research. These cameras are often rugged and weather-resistant, with features such as motion detection and infrared night vision to capture images and videos of wildlife or other outdoor activities without human intervention. Scoutek trail cameras are useful for tracking animal behavior, monitoring remote areas, or capturing images in challenging environments. They are equipped with features like long battery life, high-resolution imaging, and storage capabilities to function effectively in various outdoor conditions. These cameras can be used for recreational or professional purposes, providing a reliable way to capture outdoor activities or wildlife over an extended period.

The Implication

The partnership began with a Discovery Phase, where NorthBay thoroughly examined Scoutek's operations, focusing on the tools and technologies used to host and maintain their business and data analytics applications. These insights were crucial in designing tailored support models and assembling a support team with the right skills and expertise for Scoutek. During this phase, the MSP team also closely analyzed AWS infrastructure costs to recommend potential cost optimization strategies.

Following this, a structured transition and enablement process was established for a set timeframe. This process aimed to manage the shift from Scoutek's current operations to a more efficient future state with minimal disruption. The transition phase ensured a smooth shift, with newly implemented services aligned to Scoutek's business goals and agreed-upon standards.

Solution

NorthBay Solutions, a Premier Tier AWS Partner known for consulting and Managed Services, became Scoutek's strategic partner. With NorthBay's extensive AWS expertise, Scoutek gained a secure and efficient cloud environment.

Peace of Mind with Managed Support: NorthBay's dedicated team offers continuous support and proactive monitoring to ensure Scoutek's cloud infrastructure runs smoothly. This minimizes downtime and ensures optimal performance for critical applications.

Enhanced Security and Compliance: NorthBay places a strong emphasis on security, deploying robust measures to protect Scoutek's data and applications. This safeguards compliance with industry standards and builds trust with customers.

Cost Optimization and Efficiency: NorthBay's proficiency in cloud services helps Scoutek reduce unnecessary expenses while maximizing return on investment (ROI). This allows Scoutek to allocate resources more effectively for strategic projects.

Data-Driven Insights for Continuous Improvement: NorthBay uses its comprehensive knowledge of Scoutek's cloud setup to offer valuable insights and recommendations for ongoing improvement. This ensures Scoutek's cloud environment maintains high performance and value over time.

AWS Services

Benefits

Scoutek partnered with NorthBay's Managed Services team to unlock the full potential of their cloud infrastructure. This strategic collaboration relieved Scoutek's internal IT team from the stress of daily management, allowing them to concentrate on what truly matters:

Enhanced Performance & Uptime: NorthBay's expertise ensured Scoutek’s cloud infrastructure runs smoothly, delivering superior performance and maximized uptime. This translates to a more reliable and responsive experience for their customers.

Empowered Innovation: With NorthBay managing their infrastructure, Scoutek’s internal team gained valuable time and resources. This newfound freedom allows them to shift their focus to core business priorities, developing innovative applications and exploring new ways to serve their customers.

Resilient Infrastructure: NorthBay has established comprehensive backup services across all levels to guarantee business continuity in the event of a disaster. This strategic approach has enabled Scoutek to maintain optimal service delivery to its customers without interruption.

Meet Our Customer

Alamar Foods, a leading Saudi Arabian quick-service restaurant (QSR) operator across the Middle East, North Africa, and Pakistan, has solidified its position as a regional powerhouse for over three decades. Their success hinges on a seamless customer experience, made possible by a robust technical and digital infrastructure.

As the master franchisee for Domino's Pizza and Dunkin Donuts, Alamar Foods leverages the power of AWS cloud infrastructure. This strategic partnership allows them to host critical business and analytics applications with agility and scalability. Their approach seamlessly integrates advanced managed services, like scalable database solutions, with serverless options like Lambda. They also utilize non-managed services like EC2 for a comprehensive cloud strategy.

This enables Alamar Foods to run sophisticated business applications that are vital to their day-to-day operations. Their commitment to cutting-edge cloud solutions empowers them to deliver and analyze services with exceptional efficiency. By embracing technology, Alamar Foods demonstrates its unwavering dedication to improving service quality and achieving operational excellence.

The Implication

The partnership began with a Discovery Phase, where NorthBay gained a thorough understanding of Alamar Foods' operations, focusing on the tools and technologies used for hosting and maintaining their Business and Data Analytics Applications. NorthBay team prepared a detailed inventory covering all the AWS services which Alamar was utilizing along with the cost spent on each service. The insights obtained during this phase were crucial in tailoring support models and forming a support team equipped with the necessary skills and expertise for Alamar Foods. During this Discovery Phase the cost spent on AWS Infrastructure was also thoroughly analyzed in order to suggest the possible cost optimization options.

Subsequently, a transition and enablement process was put into place for a set duration. This process aimed to manage the shift from Alamar’s current operational state to a future, more streamlined state with minimal disruption. This phase guaranteed that the transition was seamless and that the newly implemented services were in line with Alamar’s business expectations and the agreed-upon standards.

Solution

NorthBay Solutions, a Premier Tier AWS Partner specializing in consulting and Managed Services, became Alamar Foods' strategic partner. By leveraging NorthBay's deep AWS expertise, Alamar Foods achieved a comprehensive and secure cloud environment.

Unlocking Business Value with NorthBay's Managed Services:

Peace of Mind with 24/7 Support NorthBay's dedicated team provides ongoing support and proactive monitoring, ensuring Alamar Foods' cloud environment operates flawlessly. This minimizes downtime and maximizes uptime for critical business applications.

Enhanced Security and Compliance: NorthBay prioritizes security, implementing robust safeguards to protect Alamar Foods' data and applications. This ensures compliance with industry regulations and fosters trust with customers across all segments.

Cost Optimization and Efficiency: NorthBay's expertise optimizes Alamar Foods' cloud environment, minimizing unnecessary spending and maximizing return on investment (ROI). This allowed Alamar Foods to allocate resources more effectively towards strategic initiatives.

Data-Driven Insights for Continuous Improvement: NorthBay leverages its in-depth understanding of Alamar's cloud infrastructure to provide valuable insights and recommendations for ongoing optimization. This ensures Alamar's cloud environment continues to deliver superior performance and value over time.

AWS Services

Benefits

Alamar Foods partnered with NorthBay's Managed Services team to unlock the true potential of their cloud infrastructure. This strategic move freed their internal IT team from the burden of day-to-day management, allowing them to focus on what matters most:

Enhanced Performance & Uptime: NorthBay's expertise ensured Alamar Foods' cloud infrastructure runs smoothly, delivering superior performance and maximized uptime. This translates to a more reliable and responsive experience for their customers.

Cost Optimization Powerhouse: Our Managed Services Provider (MSP) team became Alamar Foods' cost optimization heroes. We identified and implemented a staggering 30% reduction in monthly AWS expenses within the first month! But the savings continue – NorthBay continuously seeks further opportunities to eliminate waste and optimize resources, ensuring Alamar Foods gets the most out of their cloud investment.

Empowered Innovation: With NorthBay managing their infrastructure, Alamar Foods' internal team gained valuable time and resources. This newfound freedom allows them to shift their focus to core business priorities, developing innovative applications and exploring new ways to serve their customers.