Enterprise AI that ships — and stays in production.
Thest designs, builds, evaluates, and hands over agentic platforms, RAG systems, and LLM applications that survive security review, procurement, and real-world use — with full ownership transfer to your team.
Built for modern enterprise AI stacks
Most AI work dies between demo and production.
Enterprises do not need more prototypes. They need systems that pass security review, integrate with existing estates, measure quality, and remain operable after the project ends.
Pilots that never ship
Demos impress stakeholders, then stall in security review, data access, or integration work.
No release discipline
Teams scale AI usage without quality gates, regression suites, cost controls, or rollback plans.
Vendor lock and black boxes
Outsourced chatbots leave organizations dependent on a vendor and unable to operate the system.
A delivery system for enterprise AI — not another pilot factory.
Thest combines consulting depth with reusable delivery assets: reference architectures, evaluation patterns, governance templates, and operating runbooks.
RAG & knowledge platforms
Permission-aware retrieval, grounded answers, freshness, citations, and evaluation for enterprise knowledge work.
Agentic AI & multi-agent systems
Tool-using agents, orchestration, human approval, escalation paths, and operational controls for high-value workflows.
Evaluation & governance
Golden datasets, release gates, policy checks, observability, and audit-ready artifacts for serious buyers.
AI strategy to architecture
Use-case portfolios, risk models, investment logic, and target architectures executives can fund and govern.
Four gates from strategy to operated system.
Every engagement moves through explicit decisions, acceptance criteria, and handoff artifacts so stakeholders know what is ready, what is risky, and what happens next.
Scope
Business outcome, data policy, integration surface, and measurable acceptance criteria.
Build
Architecture, retrieval, agents, guardrails, workflows, and observability for production use.
Evaluate
Quality, safety, regression, latency, and cost checks before every release decision.
Operate
Code, runbooks, monitoring, security notes, and enablement so your team owns the system.
See the class of systems we engineer.
Illustrative production patterns for enterprise buyers evaluating architecture, risk, and delivery quality — before a full engagement.
Enterprise knowledge assistant
Permission-aware RAG with citations, freshness controls, and evaluation harnesses for internal knowledge work.
Operations multi-agent copilot
Tool-using agents with human-in-the-loop approval, escalation, and audit trails for operational workflows.
LLM release & quality gate
Regression suites, safety checks, cost tracking, and go/no-go release decisions for production LLM apps.
Built for organizations with real constraints.
Sensitive data, multi-stakeholder review, existing cloud estates, regulated environments, and teams that must own the system after launch.
Production-grade thinking for enterprise buyers.
Frameworks and engineering guidance that help leaders decide what to fund, what to block, and how to reach production.
Reduce ambiguity before you scale spend.
A clear commercial path from readiness assessment to discovery to production delivery — with acceptance criteria, not vague retainers.
Assessment
Clarify readiness, risk, architecture options, and the first production path — before you scale spend.
Discovery sprint
Platform map, prioritized use cases, acceptance backlog, and a commercial delivery plan.
Platform build
Accepted-delivery credits for systems that meet explicit quality and production gates.
Next step
Start with a Production Readiness Assessment.
Bring your AI roadmap, pilot, or platform idea. We return a clear view of readiness, risks, architecture options, and the first production path — so the next decision is investable.