Working agents.
Not slide decks.
Tell us how your portco actually operates. We'll tell you where AI fits, where it doesn't, and build exactly what earns back the fee. Source code yours.
Operator-built · Production Python · MCP-native · 6-week delivery
Patterns
Where AI tends to fit
After enough discovery calls, these are where AI earns its fee most often. Your portco's answer might be one of them, all of them, or none. We figure that out on the call.
Labor replacement
Agents that do the work headcount currently does: inbox triage, research, CRM upkeep, drafting, document review. Humans supervise; agents operate.
Workflow compression
A deal review that took a junior two days collapses to four minutes. Multi-step ops loops that ran weekly become real-time.
Margin unlock
We target specific EBITDA drains in the portco: customer ops, deal admin, back-office reconciliation. We build the agent that removes them.
100-day plan execution
Post-close, time matters. We scope to fit the VCP sprint: an agent live inside 6 weeks, measurable before the next board.
MCP-native integration
Agents plug into Gmail, Outlook, HubSpot, Salesforce, Pipedrive, Drive, SharePoint, Slack, Telegram. Whatever the portco runs on.
Code ownership
Source delivered at handoff. Agents run on infrastructure the portco controls. No lock-in, no hostage-taking, no vendor dependency.
Production case
Drake. Our own agent, running 24/7.
We built Drake to run our own deal operations. It's been running in production since Q1 2026. Shipped, not slide-deck.
Drake runs deal flow end to end.
24/7 inbox monitoring. HubSpot pipeline management. CIM scoring against investment criteria. Auto-drafted IOIs and LOIs. Personalized outreach at scale. A PDF daily digest each morning. Runs locally on the operator's machine, so data never leaves the operator's infrastructure.
- Inbox watch
- 24/7
- Response p50
- < 1 min
- Data locality
- 100%
Why us
An unusual stack for this work
Operator background, production engineering, and PE fluency in one shop. That combination is rare on purpose.
We listen first
Before we build anything, we listen. The first call is 20 minutes of you walking us through how your portco actually operates. Half the time what we learn on that call reshapes the proposed scope. We'd rather understand than pitch.
We ship code, not decks
Python agents. MCP-native integrations. Real systems running in production. If you want a slide deck about the future of AI, hire a consultancy. If you want an agent live next quarter, hire us.
We speak PE
Value creation plans. 100-day plans. EBITDA bridges. Dollar-weighted uplift tracked to basis points. Your IC understands what we're shipping because we scope in your language.
You own it
Source code delivered at the end of the engagement, with runbooks. No lock-in. If we part ways, the portco's agent keeps working.
How we work
Six weeks. One live agent.
Same shape every engagement. Scoped to the portco's operating cadence, not ours.
Discovery
We shadow the target operation in the portco. Inbox, CRM, documents, meetings. Identify the EBITDA-adjacent workflow where an agent earns back its fee in the first year. Scoped proposal delivered end of week. Sometimes the honest answer is that AI isn't the right lever yet; when it isn't, we say so.
Build
Agent developed against the portco's real systems. Weekly demos. Operator feedback loop. By week four you see the agent doing the job in staging.
Deploy
Agent goes live on portco-controlled infrastructure: a laptop, Mac mini, or VPS they own. Source code handed over with runbooks and a control channel (Slack or Telegram). No vendor lock-in, ever.
Start a build
Tell us the workflow.
We'll tell you if it's an agent.
20-minute discovery call. You walk us through how your portco actually operates. We tell you where AI fits, where it doesn't, and whether it's this quarter's play or a later one. Sometimes the honest answer is: not yet.
We prefer to hear the workflow before we send a deck.