Forward-deployed engineers who close the production gap.
Most AI programs die between demo and deployment. We're a team of senior engineers and operators who have shipped AI at scale — and we embed inside your stack to make sure yours doesn't.
The things we'll argue with you about.
Most of our engagements start with a CIO or CTO who's seen one too many AI demos. These are the four positions we open every conversation with.
Adoption is an engineering problem.
Slide decks don't change Monday morning. Code in your repo does. We build inside your stack, not adjacent to it.
Start with the LLM proxy.
Before agents, before fine-tuning, before RAG. Centralizing model calls behind a proxy you control is the highest-leverage first move in any AI program.
MCP changes the game — start with git.
Model Context Protocol gives agents and humans the same context surface. The cheapest place to prove it is your own git repos.
Read-only HITL beats autonomy in year one.
The safest, highest-ROI first deployment is almost always a read-only human-in-the-loop workflow. Earn the right to autonomy.
Turn ambition into working AI — not another pilot.
We started RuntimePartners because we'd seen the same pattern too many times: an enterprise buys the AI story, funds a pilot, and twelve months later has a demo that nobody trusts in production.
The gap isn't talent or budget. It's execution. Someone has to write the proxy, wire the MCP servers, instrument the workflows, and prove adoption with real telemetry. That's what we do — inside your stack, with your team, on your timeline.
No licensing. No lock-in. No retained dependency. We ship, we hand over, and we leave your engineers owning the system.
Engineers who have already shipped this.
Our engineers were forward-deployed at AI.pro, shipping LLM infrastructure and agent systems into live production environments. They learned what breaks at scale — and what doesn't.
Before enterprise, the same team shipped agentic workflows for thousands of SMBs. They learned that adoption is an engineering problem, not a training problem.
We don't do roadmaps, workshops, or "digital transformation." We deploy into your VPC, write code in your repos, and ship a workflow your team actually uses. Then we leave.