Advisory
We find where AI is worth the effort, and where it isn’t. Use-case prioritization, feasibility, operating models, architecture, readiness, and a costed business case. Then we build it.
Most AI projects stall between the demo and production.
The hard part isn’t the model. It’s building the system around it.
We are an AI engineering firm.
We are business operators, AI engineers, and domain experts. We embed with your team to build, deploy, and adapt complex enterprise software and AI systems around how your business actually operates.
Human judgment. Systems thinking. Machine intelligence.
You are the captain. We are the copilot.
What we do
Models are getting better quickly. But production AI depends on much more than the model: operational context, reliable data, process knowledge, permissions, governance, evaluation, monitoring, human oversight, and integration with the systems where work actually happens.
The next advantage will not come from simply having the best model. It will come from building trustworthy systems that can understand context, reason across workflows, take action safely, and improve over time.
We build both the intelligence and the operational system around it.
We find where AI is worth the effort, and where it isn’t. Use-case prioritization, feasibility, operating models, architecture, readiness, and a costed business case. Then we build it.
We design and build AI applications, agents, and enterprise software; integrate them with your systems and data; and put security, governance, evaluation, monitoring, and reliability around them.
Our engineers embed with your business and technical teams, learn how the work actually happens, and stay close from experimentation through reliable production and adoption.
Start where you are.
Use-case triage, feasibility on your real data, an instrumented baseline, and a costed business case.
Where most teams startOne or two high-value workflows live in production, with guardrails, evaluations, observability, human controls, and a rollback path.
The first buildReusable architecture, workflow components, shared evaluation infrastructure, common integrations, reference patterns, and the next workflows.
After the first workflowSLAs, evaluation regression, drift and quality monitoring, cost monitoring, incident response, model changes, and upgrades.
OngoingPair-building with your engineers, plus the runbooks, playbooks, documentation, and architecture your team needs to own what we build together.
Runs throughoutHow we work
If the numbers don’t clear the bar we agreed at the start, we say so and stop. Better to stop early than spend a production budget scaling something that isn’t working.
We sit with the people doing the work, understand the systems behind it, and establish the baseline we will be measured against. If the foundation is not ready, we fix the necessary data paths, deployment paths, instrumentation, tests, and integration points before building anything on top.
Before anything gets authority to act, we test it against your own case history and live workflows. We measure how it performs before it touches production decisions.
It goes live with approval thresholds, permissions, audit trails, monitoring, fallback behavior, and rollback. We give it more room only when the numbers hold up.
Your engineers build alongside ours from the beginning. The tests, runbooks, architecture, documentation, and operating knowledge stay with you.
Measure first. If we can’t establish a baseline, we won’t pretend to scope an outcome.
Tests ship with the system. Evaluations run again whenever the system changes.
Security starts on day one. Permissions, auditability, governance, and rollback are architecture, not retrofit.
Model- and cloud-neutral. We don’t resell licenses, so we have no reason to over-specify a particular platform or model.
Shared risk. Where it makes sense, a meaningful portion of our fee rides on the metric we agree at the start.
Your system stays yours. Your data, settings, business logic, documentation, and operational knowledge remain yours.
Team
Our core team includes technology leaders, engineers, and operators who have built and run enterprise systems at Fortune 500 companies including Cisco and UnitedHealthcare, and at startups.
Senior technology and operating leaders with experience across the US, APAC, and Europe. Kellogg MBAs with experience leading global engineering teams, carrying P&Ls, and engaging with boards and executive teams.
AI, data platforms, cloud, distributed systems, networking, enterprise software, process automation, IoT, and wearables.
Builders. Buyers. Advisors. A 360-degree view of how technology is evaluated, funded, built, deployed, operated, and adopted inside enterprises.
Inference, model usage, infrastructure, observability, and architecture choices cost money every day a system runs. We understand what systems cost to build, and what they cost to operate.
We staff to the problem and the outcome. If a capability isn’t needed for your workflow, it isn’t on the invoice.
An hour on a call, and we’ll tell you what we’d prioritize.