The challenge

As their core markets became saturated, the company saw declines in sales.

The internal business consultants (account managers) who drove account and distributor growth, optimized performance, and guided distributors had the power to reverse this trend in theory but were constrained by their workflow in practice.

They spent 40-50% of their time analyzing information by manually

• Reviewing reports  

• Tracking key performance indicators (KPIs)

• Connecting data and insights from multiple systems

This led to

• Limited time for coaching and strategic work  

• Inconsistent quality of recommendations  

• No standardized way to evaluate and develop accounts  

To revitalize growth, the company needed to fundamentally rework they managed accounts.

From data foundation to AI opportunity

During the initial phase of this project, KIS built a centralized data layer to unify and structure data from multiple internal systems.

After a fast and reliable delivery, when the idea of introducing AI emerged, the client continued working with KIS. They chose us not only due to prior delivery success but also for our ability to identify practical AI opportunities and translate them into real business solutions. The challenge was both technical and strategic. How could we turn “build a chatbot” into something that meaningfully improves the business?

Defining and building in parallel

KIS took an active role in shaping the product and worked as an extension of the client's team. Instead of waiting for specific requirements, we

• Translated business goals into real-world use cases  

• Grounded development in the daily workflow of account managers  

• Iterated quickly, refining both the product and its architecture

Working with AI means defining both what to build and how to build it (architecture decisions, model selection, and validation strategies). Given the evolving nature of AI, we tested, adapted, and, in some cases, rebuilt multiple approaches. This iterative process allowed the team to move forward without strict criteria while still ensuring the solution aligned with real business needs.

The solution: AI embedded into daily workflows

We created an AI-powered account management platform that integrates data and analytics into a single workspace. At the core of this system is the Account Analyzer: an AI chatbot embedded directly into the account manager’s workflow.

Instead of manually analyzing multiple data sources, account managers can now get clear, actionable guidance in seconds.

Here are just some of the Account Analyzer’s use cases:

• Preparing for a distributor meeting (“What should I focus on?”): The system highlights key risks, opportunities, and recommended actions.  
• Analyzing account performance at scale: The system evaluates 100+ data points to identify patterns, gaps, and growth opportunities.  
• Prioritizing accounts: The system enables more targeted actions by identifying accounts with low performance currently but high potential.
• Comparing accounts: The system benchmarks performance against multiple profiles.

The platform transforms complex, real-time data and internal business knowledge into decision-ready insights, reducing analysis time from hours to less than a second and enabling faster, more consistent actions.

How the solution delivers business value

The platform's intentional design and integration enhance the business in several tangible ways.

• AI grounded in real business context: Using a retrieval-augmented generation (RAG) architecture, the platform creates outputs based on trusted internal business data and company knowledge instead of generic responses.

• High-quality and reliable outputs: Our custom validation frameworks achieved over 90% accuracy and uncovered previously undetected data issues.

• Modern, flexible architecture: The platform can continuously evolve as new AI use cases, workflows, and analytics capabilities emerge.

• Business autonomy and scalability: Business teams can add use cases and refine the system over time, reducing dependency on technical teams and enabling sustainable AI adoption at scale.

Rather than using AI for experimentation alone, KIS embedded AI where it directly impacts business performance, instead using experimentation to organically reach a clear and defined goal. Most importantly, the platform enables a structural shift: from manual, fragmented analysis to a scalable, standardized way of driving performance.

What it takes to make AI work

Many organizations treat AI as a standalone initiative, often starting with generic tools like chatbots, without properly connecting them to real workflows or reliable data. The result is low adoption rates, inconsistent outputs, and limited business impact.

For this project, we project treated AI not as a feature but as part of a broader strategy that involved opportunity identification, solution design, and continuous iteration. KIS contributed to every aspect of AI deployment:

• Identifying where AI could create value  

• Defining the right use cases and product direction  

• Designing and implementing the solution  

• Ensuring reliability, scalability, and adoption  

While this solution was designed for account management and distributor growth, the underlying approach is applicable across industries and business functions. Organizations that rely on data analysis, operational workflows, and decision-making at scale can use AI-powered data aggregation and real-time intelligence to reduce manual effort, accelerate onboarding and training, and enable teams to focus on higher-value strategic work. Overall, this leads to faster insights, more scalable operations, and better business decisions