RAG Systems
Retrieval-augmented generation with hybrid search, source quality controls, and evaluation hooks built in.
Learn moreApplied AI Engineering
Turn AI Pilots Into Production Systems.
We scope, build, evaluate, and hand over reliable LLM systems your team can operate independently.
Built on Leading AI Infrastructure
What We Build
Production-grade LLM systems across retrieval, agents, and evaluation — engineered for reliability from day one.
AI Agents
Multi-step agentic workflows with tool integration, checkpoints, retry logic, and human-in-the-loop governance.
Learn moreEvaluation & Reliability
Continuous quality scoring, regression detection, and production readiness baselines across every release.
Learn moreHow We Work
Every engagement follows our Reliability Loop — four stages with explicit gates, artifacts, and handoff.
1
Scope
Align on measurable outcomes, map dependencies, and lock acceptance criteria before a single line ships.
2
Build
Engineer with retries, fallbacks, and observability. The default target is production reliability, not demo polish.
3
Evaluate
Run evaluation harnesses and regression tests each sprint so quality issues surface before release windows.
4
Operate
Hand over code, runbooks, and response procedures so your team can run the system independently.
Why Teams Choose Thest
You don't need more AI activity. You need fewer failure points between roadmap and production.
Quality Built Into Every Sprint
Automated scoring and regression checks run continuously — not bolted on before launch.
No Vendor Lock-In
Code, runbooks, and architecture context transfer to your team. You own everything we build.
Transparent Pricing
Credit consumption maps directly to accepted scope. No surprise invoices, no ambiguous hours.
Ready to close your reliability loop?
Bring your current AI roadmap. We'll convert it into a production-ready plan with explicit acceptance gates and operational handoff.