AI automation
Turn a slow, manual workflow into one that runs itself, with checks you can see.
- A running automation in your environment, not a slide
- A short runbook: how it works, where it stops, how to change it
- The eval suite that gates it
Services
AI that ships, then keeps its word
Four headline services, AI-first, with cloud and security-engineering depth underneath. Each one is scoped, embedded with your team, and checked against an honesty gate before it reaches your users.
The four services
Forward-deployed AI engineering
We embed with your team and ship inside your stack.
- Production code in your repositories, reviewed and documented
- The infrastructure to run it, or integration with what you have
- A team that understands the system because they watched it get built
AI agents and grounded RAG
Answers pulled from your own documents, each traceable to its source.
- A working agent or ask-anything surface over your data
- A citation trail from every answer to its source document or row
- A retrieval setup you can extend as your corpus grows
LLM evals and reliability
Honesty gates that block a wrong answer before it ships.
- A repeatable eval suite wired into your change process
- A gate that blocks a regression from reaching users
- A measured honesty baseline you can hold the system to
Supporting capabilities
The engineering depth underneath the AI
The AI sits on real infrastructure, and we run that too. These are not headline services, they are the foundations that make the headline services trustworthy.
The infrastructure underneath
We run the cloud your agents sit on, and fix it with diagnosis instead of bigger boxes.
- Cut a production cloud bill 60 percent in one evidence-first audit, zero new capacity
- Drove a flapping API's p99 latency down 77 percent with config, not compute
- Monitoring and budgets set up so the next problem pages the right person
AI for smart-contract security
Multi-agent systems that audit smart contracts and surface real findings, where AI meets web3.
- A multi-agent pipeline that runs several models against each other on the same target
- A seven-gate stack every candidate finding clears before a human sees it
- Real high and medium findings on live, audited DeFi protocols
Start a project
Name the workflow that eats your team's week
Name the workflow that eats your team's time. We will tell you honestly whether AI fits, and if it does, scope a first piece with a known price.