Ask Your Sales Forecast a Question, Get a Plain-Language Answer
A sales forecasting system for FMCG that predicts future sales with machine learning and lets anyone ask questions about the forecasts in plain language.
A good forecast that sits in a report nobody can query
FMCG businesses sell many products across many channels and regions, and demand shifts with seasons, promotions and local events. Forecasts are often built in spreadsheets with simple rules that miss these patterns. Even a good forecast sits in a report or dashboard, so business users wait for an analyst to run the numbers and decisions rely on gut feel.
Want Forecasts Your Own Team Can Query in Plain Language?
We'll scope a pilot around your exact sales data and planning process — evaluated ML models plus a reasoning agent — with clear success metrics before any production commitment.
An end-to-end forecasting system with a conversational front end
Forecasting models
Multiple machine learning models trained and evaluated on historical sales data and compared to find the ones that predict most reliably.
AI agent for natural-language queries
A reasoning agent understands a question, decides whether a new prediction is needed, triggers the forecasting models when it is, and answers with insights from the results.
How it works
ML models produce the numbers and the AI agent decides when to use them and explains them. Trained models predict future sales, validated on historical data — not the language model. Evaluation during training chooses the most accurate model from measured results. The agent reasons step by step, calls the right tool and turns forecast output into plain-language insight. Business users plan and decide.
A typical query
- 1A user asks how a product is expected to sell next month
- 2The agent works out what it needs
- 3If a forecast is needed it triggers the prediction models
- 4It interprets trends, changes and risks
- 5The user gets a plain-language reply and can ask follow-ups on the same results
What users get
- Sales and planning teams get forecasts on demand without waiting for an analyst
- Supply chain and production get better demand estimates for stock and production decisions
- Managers get plain-language insights, not just tables
Trust
Models are evaluated against each other, so the one in use is chosen on evidence; forecast values come from the trained models and the agent only calls them and explains; the agent works in visible steps, so it is clear which tool was called and why; forecasts inform planning and people make the final calls.
Status: done — a forecasting system for FMCG with multiple ML models trained and evaluated, and an AI agent handling natural-language queries, triggering predictions dynamically and giving insights. Which models were compared and which performed best, accuracy metrics, data used and its granularity, and next steps are still to confirm.
An engineering team that ships evidence-based forecasting, not slide decks
AWS Advanced Tier Partner
Certified cloud and AI delivery, so your forecasting system runs on infrastructure built to AWS Well-Architected standards from day one.
Pilot-first engagement
We scope, build and validate against your real historical sales data before you commit to a production rollout.
Models chosen on evidence, not guesswork
Multiple ML models are trained and evaluated against each other, so the one in production is the one that measurably predicts best.
Visible, explainable agent steps
The agent works in visible steps, so it's always clear which tool was called and why — forecasts inform planning, people make the final call.
Trusted by forward-thinking teams
AWS-Certified Experts Delivering Cloud Excellence.
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Actually Ask Questions About?
Tell us about your sales data and planning process — we'll help you scope a forecasting pilot with evaluated ML models and a natural-language agent.