These describe the kinds of systems we build. They are not a list of named client projects, and they do not include invented results.
Conversational AIProblem
A product team is spending too much time on the same documentation questions.
Approach
A context-aware assistant with retrieval over product docs and a path to a human agent.
RAGProblem
Useful answers already exist in internal documents, but they are hard to find during delivery.
Approach
A retrieval assistant with citations over a defined corpus the partner controls.
Conversational AIProblem
A service team misses routine booking or FAQ calls outside working hours.
Approach
A voice workflow that captures intent, answers common questions, and hands off exceptions.
AnalyticsProblem
Leadership can see last month clearly, but not a defensible view of what is likely next.
Approach
A forecasting surface that combines existing operational data with a review-friendly dashboard.
Predictive AnalyticsProblem
Planning still depends on static spreadsheets while the useful history already exists.
Approach
Time-series models with scenario views the operations team can inspect.
Predictive AnalyticsProblem
Inventory decisions are too coarse for the number of products and locations involved.
Approach
A demand model broken down to the grain the partner’s client actually plans against.
BIProblem
Weekly reporting is assembled by hand from several systems.
Approach
A warehouse plus dashboards that reuse the same metric definitions.
AutomationProblem
Market or research data is collected manually and goes stale between pulls.
Approach
A scheduled, structured collection pipeline with a delivery format the rest of the stack can use.
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