AI Applications Built Around Your Data
Assistants, search, and forecasting are only as useful as the data underneath them. We build these on a foundation you can trust, and start small.
Common kinds of AI applications
Each one is shaped around a specific business problem. They all share the same data foundation, so the second one is easier than the first.
Chat Applications
A branded assistant for customers or employees, grounded in your product and policy documentation.
Enterprise Search
Unified search across wikis, drives, and ticketing systems that respects existing permissions.
Document Intelligence
Extraction and classification pipelines for contracts, invoices, and compliance filings.
Recommendation Engine
Personalized product or content recommendations trained on your first-party behavioral data.
Forecasting
Demand, revenue, and staffing forecasts refreshed automatically as new data lands.
Knowledge Base
A living, searchable knowledge base that stays current as source documents change.
Internal AI Portal
A single, governed entry point for employees to access every internal AI tool.
Executive Dashboard
Natural-language querying layered on top of your existing BI and warehouse investment.
One foundation, many applications
Applications share the same data layer, search infrastructure, and monitoring. That keeps things consistent and means you aren’t rebuilding the basics each time.
- → Vector Search & retrieval infrastructure shared across applications
- → Unified authentication and role-based access control
- → Centralized observability, evaluation, and cost tracking
- → Reusable UI component library for consistent experiences
Have an application in mind?
Tell us what you're trying to do. We'll look at the data behind it and suggest a realistic first step.