Failure mode
Agent flows only work when someone watches them.
Retries stack, prompts drift, and the demo path starts leaking in production.
Production reliability for AI teams
Make your AI system reliable in production.
We diagnose the weak point in live AI systems and ship the fix without forcing your team into a rewrite.
Tools & platforms we build with
The breakpoint
There's a stage where every serious AI team stops asking “can we launch this?”
The harder question is whether the system still holds when traffic, edge cases, billing, and dependencies all show up together.
Hidden cost
Inference spend climbs before reliability improves.
More models and glue code pile on while the system stays opaque.
Org symptom
The product team becomes incident response.
People babysit automation instead of improving it. Velocity and confidence fall together.
The first week
We do not start with a statement of work. We start with the system.
The process is designed to compress ambiguity quickly and move from diagnosis to implementation without wasting the client's time.
01
Diagnostic
Typically 3-5 days
Read the system before prescribing the fix.
You walk us through the stack, the workflows, and what keeps failing. We inspect the architecture, code paths, prompts, integrations, and operational realities rather than starting with assumptions.
Live process
week one
Step 1
01
Audit inputs
02
Workflow map
03
Failure list
02
Intervention
A crisp action plan with technical tradeoffs
Identify the highest-leverage intervention.
We do not hand over a generic report. We isolate the issue that matters most right now, whether that lives in orchestration, model selection, fallback behavior, observability, or team workflow.
Live process
week one
Step 2
01
Priority path
02
Tradeoffs
03
Execution order
03
Delivery
Weekly syncs, async visibility, production-ready delivery
Ship the change and keep you informed.
We implement with your team in view: direct updates, clear reasoning, full documentation, and no mystery process. The work stays operationally useful after we leave.
Live process
week one
Step 3
01
Build status
02
Async updates
03
Delivery handoff
Standards
What we won't do.
We won't pitch a rewrite.
If your system works, it stays. We're here to refactor and improve what exists, not propose a ground-up rewrite. We've shipped enough production AI to know the difference between real problems and shiny-object rewrites.
We won't disappear.
You'll know what we're working on, what we've found, and what's next. We document what we build so your team can maintain and extend it. No black boxes.
We won't treat your money like it's infinite.
We manage API budgets, optimize inference costs, and scope tightly. If a feature isn't worth the compute, we'll tell you before building it. Every hour should be traceable to a result.
We won't overstay.
If we solve the problem and you don't need us anymore, we'll say so. If we're not the right fit, we'll tell you in the first week. Not the third month.
Final checkpoint
If your AI system works in demo mode but breaks once real traffic shows up, that is the conversation to have.
Bring us the architecture, the workflow, and the mess as it actually exists. We'll tell you what we'd tackle first and whether we should be the team to do it.
Response within 24 hours. Clear fit or clear no.