kognate.ai

Work that shipped

Not concepts. Not decks. Systems in production.

A few of the projects we can talk about openly. Most of our work sits behind NDAs — happy to walk through more privately.

01 · Data Center · Enterprise Analytics

From Spreadsheet Chaos to AI-Powered Operations

The Mess

  • Global data center operator drowning in manual spreadsheets and data silos
  • Legacy Power BI built with brute-force ingestion — weeks to change anything
  • No unified view of capacity, contracts, or operations across regions

What We Built

  • Unified Azure data platform with real-time and batch pipelines feeding Data Lakes and Fabric
  • Standardized hierarchies and tracking across departments
  • AI copilots so operators query data in natural language instead of waiting for reports

Results

  • Unified visibility across 4 time zones for the first time
  • Weeks of manual analysis replaced with real-time copilot queries
  • Customer response times improved — no more stale capacity data
  • Scalable platform that grows with the business, not against it

02 · Consumer AI · 0→1 Product Build

AI Product with Persistent Memory — Concept to Production in 5 Weeks

The Challenge

  • Build an AI assistant that learns per-user over time — not a stateless chatbot
  • Remember context across sessions and retrieve relevant information on demand
  • Keep API costs predictable enough to scale without blowing the unit economics

What We Built

  • Three-tier memory: sliding conversation window, compressed cross-session memory, semantic fact retrieval
  • Token-budgeted context capped at ~8K per request to control cost
  • Async pipeline that converts conversations into searchable structured data

Results

  • Concept to production in 5 weeks, solo build
  • AI that compounds intelligence per-user over time
  • All-in cost: $1.18 per active user per month
  • Architecture designed for scale without cost explosion