Why most "AI hires" fail after 3 months.
These are the problems teams run into when they try to build AI without the right specialist.
They know LangChain basics but can't handle concurrency, rate limits, or fallback logic.
No one monitored context window usage; your AWS bill tripled in week two.
They built it, but have no framework to measure if it's actually getting better.
AI costs are harder to predict than expected.
Tightly coupled to one model provider; migration takes months when APIs change.
They can build a demo, but struggle to turn it into a reliable, scalable production system.
A working AI demo and a production-ready AI feature are two different disciplines. We place developers who understand the difference.
Built for teams ready to move from AI ideas to real products.
If you know AI can improve your product but need the right technical expertise to build it, this is for you.
Compliance-Sensitive Enterprises
You need audit trails, PII redaction, and deterministic outputs, not just "cool AI."
Scale-Ups Post-Prototype
Your MVP works, but latency is 4s and costs are $5k/mo. You need optimization, not new features.
Product-Led AI Companies
AI is your product. A bad hire doesn't just delay a feature; it churns out customers.
We Vet for System Design, Not Just API Calls.
We test how developers design, build, evaluate, and scale AI systems in production.
RAG Architecture That Actually Works
We test chunking, hybrid search, re-ranking, and retrieval strategies—not just vector database integration.
Evaluation That Measures Results
We test hands-on experience with RAGAS, TruLens, or custom datasets to measure AI quality.
Production Observability
We test experience with LangSmith, Arize, tracing, and production debugging.
Cost Engineering
We test how developers use caching, model routing, and distillation to reduce inference costs.
Production-Ready Architecture
We test how developers handle concurrency, rate limits, fallbacks, model changes, and scaling.
Evaluation Before Launch
We test how developers identify edge cases, failure modes, and quality issues before release.
Build in-house, hire a generalist, or match with CrecenTech.
The right AI expertise can determine your project’s reliability, cost, and speed to launch.
From AI idea to production-ready feature.
Everything you need to build AI with confidence.
CrecenTech is the engine that drives our success from start to finish. They communicate effectively and always look for ways to innovate and deliver better.