A model deployment that’s actually yours.
We pick the right model for your workload — Claude for nuance and tool use, GPT for breadth, Gemini for multimodal — and run it inside your account. No re-selling, no markup, no shared keys.
Enterprise AI Integration
AI deployed as your invisible Chief of Staff.
Claude, GPT, and Gemini wired directly into your operational data — parsing the noise, drafting the work, teeing up the decisions. You only have to hit “approve.”
Anthropic ClaudeOpenAIGoogle GeminiMCPAgent SDKMake.comn8nSupabase
You need this if your highest-paid people are doing the dumbest work.
AI integration isn’t a chatbot, and it isn’t a Slackbot. It’s a system that reads what your team reads, writes what your team writes, and makes the same judgment calls your team makes — supervised, logged, and continuously improved.
We get hired when the cost of a bad decision is high enough that you can’t blindly automate it, and the volume of decisions is high enough that humans can’t keep up. Common signs:
- Your team is hand-summarizing call transcripts, contracts, or tickets nobody else has read.
- Email and Slack drafts get rewritten three times before they go out, by the person whose hour costs the most.
- Inbound requests pile up because triage is a human bottleneck.
- You’ve tried a chatbot. It made things worse.
Six concrete deliverables. No vapor.
Tool use, retrieval, and structured outputs.
The model talks to your CRM, your docs, your ledger. It doesn’t just chat. We design the tool surface, write the schemas, and constrain the outputs so the system never returns an answer you can’t consume programmatically.
Retrieval over the docs you already have.
Tickets, contracts, SOPs, transcripts — indexed, embedded, and queried with citation. Hallucinations get logged with the source the model leaned on so you can verify or correct.
Human-in-the-loop where it matters.
Drafts, not sends. Recommendations, not decisions. The system writes the email, prepares the contract, scores the lead — and waits for the human to approve. Optional auto-send for low-risk paths once you trust them.
Evals, prompt versioning, and observability.
Every prompt is version-controlled. Every run is logged. We ship a small eval harness with the deployment so you can measure quality, catch regressions, and tune over time — not pray.
Documentation and a clean handoff.
You get a runbook. A future engineer (or future Claude) can read it and understand what we built and why. The handoff is the deliverable, not an afterthought.
Drafts. Not sends.
Inputs from your real operational surface. A model with constrained tool access and your retrieval index. Outputs that go to a human-approval queue, an auto-send path for trusted flows, or a structured store the rest of the system can read.
Every step logs its inputs, its tools called, its citations, and its outputs. Audit trail is a first-class deliverable.
DEP.01
Six weeks, written down. No surprises.
-
Systems Audit
Free 30-minute call. We map the bottleneck and tell you whether AI is the right tool. If it isn’t, we tell you that.
-
Diagnose
Working sessions with the people doing the work. We watch the workflow, identify decision points, and write down what “good” looks like.
-
Architect
Model selection, tool design, retrieval scope, eval criteria. You get a written architecture you can read in 20 minutes and a fixed-fee build estimate.
-
Build
We stand up the deployment in your accounts. Daily standups, working code at the end of every week, evaluation against the criteria from week one.
-
Tune & Ship
Production rollout in stages: shadow mode, then human-approved, then auto-send for paths that earn it. Documentation lands here.
-
Care
Optional retainer for monitoring, evals, and tuning as your data and tools change. Or we hand it off clean and you take it from there.
The questions you’d ask on a call.
Are we going to be locked into one model vendor?
No. We architect against the model interface, not the vendor. Switching from Claude to GPT (or running both in parallel for evals) is a config change, not a rebuild. We've migrated production deployments across vendors more than once.
How do we know it’s actually accurate?
We ship an eval harness with the deployment. You define what good looks like in week one (with our help), and we measure every prompt change against it. Production runs are logged with their inputs, outputs, and the documents the model cited — you can audit any decision after the fact.
What about our data? Where does it go?
Inside your accounts. We deploy under your Anthropic / OpenAI / Google API keys, your Supabase project, your storage. We don’t centralize, broker, or cache your data. If you have a BAA or zero-retention requirement, we set that up at the model-vendor level.
How long until something works?
Two weeks to a working deployment in shadow mode. Six to seven weeks to production with human-in-the-loop approvals. Faster engagements are possible for narrow scopes; we will tell you on the audit call.
What does this cost?
A typical Enterprise AI Integration project lands between $25K and $80K depending on scope, with a fixed-fee build after the diagnosis week. Optional retainer afterward starts at $4K/mo. We will quote precisely after the audit.
Can we host the models ourselves?
For most workloads, no — the frontier closed-source models (Claude, GPT, Gemini) deliver a level of capability that current open-source models can’t match for production use. We can architect for self-hosting if your compliance requires it, but we’ll tell you what you’re trading away.
What if we already have an AI feature that’s not working?
We do triage engagements. A two-week diagnostic where we audit the existing deployment, write up what’s broken and why, and either fix it or recommend you turn it off. Half-billing applies to the fix engagement if you go forward.
What working with us looks like.
$25K – $80K
Fixed-fee build after the diagnosis week. No surprise invoices.
6 – 7 weeks
From signed SOW to production rollout. Faster on narrow scopes.
From $4K / mo
Monitoring, evals, tuning. Cancel anytime, no clawback.
Model API costs · net-new SaaS subscriptions · offshore staff aug
We only spend money you’ve approved.
Tell us where AI shouldn’t be.
Half the value of an audit is hearing where AI doesn’t belong in your stack. We’ll do that work in 30 minutes, on the house.