AI Engineering
Production agents, not another demo
We ship agentic systems that survive contact with real users. Claude-integrated apps, RAG pipelines, MCP servers, and evals — designed for the compliance conversation you'll have on day two.
ISO 9001 Certified
Clutch 5.0 RatedMost enterprise AI initiatives don't fail in the demo — they fail in the ninety days after it, when identity, memory, and permissions meet reality. That is where we build. Greelow ships agentic systems that operate on real credentials, remember who each user is, and log what they did — because that is exactly what your security team is going to ask about.
We are not learning this on your budget. The agentic operating system we run for a private-markets firm handles multi-channel agents with per-user OAuth credential isolation — read the case study; every architectural claim in it points at code running in production today. The same discipline shapes every engagement: evals first, least privilege, audit posture from day one.
Engagements run from a two-to-four-week prototype sprint to a full production platform. Whatever the size, the deliverable is the same kind of thing: a system your team can own, with the runbooks and eval suites to keep it honest after we leave.
Capabilities
What we build
Agentic platforms
Multi-tenant, per-user OAuth credential isolation, MCP-based tool servers.
RAG systems
Retrieval-augmented Q&A over your knowledge base, with citation and eval loop.
Claude-integrated apps
Web and mobile apps with Claude as a first-class component, not a bolt-on.
Evals and observability
The measurement layer that separates "it works in a demo" from "it works in production."
MCP servers
Connect your Claude, Cursor, or agentic app to your internal systems safely.
Architecture that survives audit
Guardrails, logging, and permission boundaries documented from day one — not bolted on when procurement asks.
Fit
Who this is for
Head of AI at a regulated-industry buyer
You need agentic systems that pass your risk team's review. The credential model, the audit trail, and the guardrails have to be right from day one.
CTO with a failed AI pilot
You've tried and it didn't ship to production. You want a partner who has actually done it — not another consultancy learning on your budget.
Product leader with a Claude/Cursor-native product idea
You want to ship something real, not another chatbot. We build agents that operate on your data with the credential model you'd have signed off on.
Process
How an engagement runs
Week 0
Discovery & architecture
Use case, data reality, guardrails and evals target — mapped with your team before anything gets built.
Weeks 1-2
Working prototype
A real agent operating on your systems, behind least-privilege credentials from day one.
From week 3
Eval-gated build-out
Golden-set regression tests gate every prompt and model change on the way to production.
Handoff
Production, documented
Runbooks, audit posture, and training so your team owns the system — not us.
Engagement shapes
Agentic prototype sprint
$40K–$80K · 2–4 weeks
Working agent, architecture doc, evals
Compliance-aware LLM rollout
$150K–$300K · 8–12 weeks
One production agent with guardrails + audit posture
Production agentic platform
$400K–$1.5M · 3–6 months
Full multi-tenant agentic OS for your domain
Tooling
The stack we bring
Models & APIs
Retrieval & data
Agent infrastructure
Agentic systems in production
A private-markets firm
How we built an agentic operating system for a private-markets firm
A field report on multi-channel agents, per-user credential isolation, and the discipline behind a working agentic system in regulated finance.
OneReach.ai
Enterprise Conversational AI Platform
Embedded a dedicated team inside a conversational-AI platform that shipped NLP pipelines, IVR systems, and LLM integrations end to end.
Common questions
- You can do both. Staff augmentation gives you the person. AI Engineering gives you the shipped system — architecture, evals, guardrails, deployment — designed and delivered end to end. Most of our clients start with one and add the other.