For ops-heavy teams drowning in repetitive work
Automate the expensive, repetitive work — end to end.
What this fixes
Your team loses hours every day to work software should be doing — copying between systems, re-keying data, chasing approvals. Most "AI automation" only handles the easy 80% and hands you back the error-prone 20%, so the manual process never actually goes away.
- 01
Copy-paste between systems
Skilled people spend their day moving data your tools should move themselves.
- 02
Half-automations that don't stick
A copilot handles the easy part and leaves every exception back on your desk.
- 03
No line of sight on the cost
You feel the drag but can't see the hours or dollars it's quietly burning.
We automate a whole business process end to end — deterministic where it must be reliable, AI only where it earns its place.
Map the real process first
We model the actual workflow, exceptions included, before automating a single step.
Deterministic core, AI at the edges
Reliable workflows do the heavy lifting; models handle judgment, never the critical path.
Wired into what you run
Deep integration with the CRMs, ERPs, data warehouses, and internal apps you already use.
Everything in the engagement
Whole-process automation
We map a real business process and automate it end to end — not a partial copilot that leaves you the hard 20%.
Deterministic, AI where it earns it
Reliable workflows do the heavy lifting; AI steps in only where it genuinely adds value.
Deep system integration
Wired into the tools you already run — CRMs, ERPs, data warehouses, internal apps.
Tracked outcomes
Every engagement reports the number that moved: hours saved, cost cut, throughput up.
What teams get
- 0%+
- of manual effort removed on automated processes
- 0/7
- workflows running without a person in the loop
- 0+
- projects delivered across industries
From first call to first release in weeks
A Pod embeds in your stack, narrows the work to the metric that matters, and ships the smallest system that moves it.
- 01
Scope the outcome
We pin the metric that matters and what "done" means — before any code.
- 02
Stand up a Tuned Pod
A senior engineer steering a proprietary in-house agent harness (Claude, Codex, Gemini), embedded in your stack within days.
- 03
Build & ship
A working system in front of real users in weeks — the agents do the building; our engineers own every call that carries risk.
- 04
Measure & improve
We track the number it moves and sharpen it as your data and the models change.
Built on what you already run
FAQ
- What kinds of processes can you automate?
- Document-heavy, multi-step, repetitive workflows across ops, finance, support, and data — anywhere people copy between systems.
- Will it integrate with our existing tools?
- Yes — deep integration into CRMs, ERPs, data, and internal tools is the core of the work, not an add-on.
- How do you keep automation reliable?
- Deterministic workflows by default, AI only where it earns its place, with monitoring and human-in-the-loop on the exceptions.
- How do you measure success?
- We agree the metric up front — hours saved, cost cut, throughput — and track it through to production.
Tell us the outcome you need.
Book a 30-minute call. We’ll map the highest-impact system to build first — and what moving that number is worth.