We Build AI That Delivers ROI
Not Just Demos
We embed a dedicated AI engineer in your organization to build custom agents for your actual workflows — proven with evals against your real data, hardened for compliance, and built to hold up long after launch.
A workflow tool with a prompt attached isn't engineering—it's a demo.
Someone strings together a workflow tool and a language model, records a 90-second demo, and calls it “AI automation.” Then it meets your actual data, your edge cases, your compliance requirements—and it falls apart.
No Debugging
No way to debug it, no way to test individual pieces.
Fragile Systems
It works on camera. Then it meets your real data and falls apart.
No Way to Verify
No evals, no benchmarks, no ground truth. You're trusting it works — with no way to prove it.
No Compliance
Compliance requirements ignored until they become blockers.
We embed an AI engineer inside your organization.
A dedicated AI engineer and part-time product manager map your actual workflows, identify high-value automation opportunities, and build custom AI agents — with evaluation suites to prove they work before they go live.
Explicit State Management
Agents with clear state machines, not spaghetti prompt chains. Every transition is logged and observable.
Full Observability
When something goes wrong, you know why. Every component instrumented, every decision traced.
Secure & Compliant
Isolated credentials, real data evaluation, compliance guardrails built in from day one.
Human-in-the-Loop
Checkpoints for human approval where they matter. Your team stays in control of critical decisions.
Full Source Code Handoff
Everything runs in your environment. No vendor lock-in. No black boxes. Your code, your infrastructure.
Evals-Driven Development
We write evaluation suites against your real data before shipping. You don't wonder if it works — you have it proven.
This might be you if...
We work best with organizations that have real workflows worth automating and care about production quality, not just demos.
Let's talk about your use caseYou've tried AI tools that didn't stick
Your team is drowning in repetitive work, but your processes are too specific for off-the-shelf
You don't have in-house AI expertise and don't want to build a team from scratch
You want AI that integrates with your systems and stays in your environment
A proven process, not a blank page.
Discovery Sprint
We interview your team, shadow workflows, and identify the highest-value automation opportunities.
Build & Iterate
Starting from our accelerator kit — proven production patterns. We design, build, and run evals against your real data — so you know it works before it goes live, not after.
Handoff
We document everything and train your team to maintain and extend what we've built. Or we stick around — your call.
We choose partners who share our commitment to intentional systems.
These aren't logo placements. These are the companies whose tools and philosophy we use to build production AI systems.
What they do
LittleHorse builds workflow orchestration infrastructure that lets engineers define complex processes with clarity and precision.
Why it matters
We use LittleHorse to orchestrate AI agent workflows because intentional systems require intentional infrastructure. No guesswork, no black boxes—just observable, debuggable orchestration that scales.
Building AI agents without proper orchestration is like building a distributed system without monitoring. You need visibility into every step, every decision, every failure mode.
Colt McNealy
CEO, LittleHorse
What they do
UltraSafe provides specialized expert model swarms that can be fine-tuned on enterprise data within secure, isolated environments—running end-to-end infrastructure on-premises or in private cloud.
Why it matters
Security is just the foundation. UltraSafe's context-specific models improve agent accuracy while reducing compute costs through efficient architecture and outcome-aligned pricing. When AI needs to work with sensitive data, specialized models outperform general LLMs in both performance and economics.
Enterprises don't just need secure AI—they need AI that actually works better. Specialized expert models fine-tuned on internal data deliver higher accuracy at lower cost than general LLMs, all while keeping data where it belongs.
Raaid Hossain
CEO, UltraSafe
Production AI, not demos.
Customer Service AIBuilt a production customer service AI to replace their Zendesk bot. The difference wasn't more sophisticated models — it was mapping their actual support workflows, building an eval suite against real support data, and instrumenting everything so they can see exactly what's happening.
Evaluated against their real support data before going live.
Operations AICurrently building production AI for their operations team — observable, durable workflows with human-in-the-loop approvals, integrated with their existing tooling.
Evals against real data, observable workflows, human-in-the-loop approvals.
Let's build AI that actually works in production.
We'll start with a conversation about your workflows, your pain points, and where AI can genuinely make a difference. No sales pitch.
Happy to connect you with current clients for reference.