No fake logos. No round ROI numbers. Here's what we can actually show you.
Our buyers are cynical for good reason. They've been burned by AI tools that had impressive logo slides and zero staying power. So we don't do logo slides. We show you the code, the market evidence, and — for qualified prospects — a peer-stage reference call with someone in your seat.
The code is the proof.
Everything we claim to do, you can see working. Three open-source repos. Public. Inspectable. No 'proprietary technology' claims. No 'trust us.' Just working software.
- PythonMIT
hubspot-claude
The product, in public.
44 agents, 75 tools, human approval required for every action.
View on GitHub - TypeScriptMIT
promptmetrics
The governance layer.
Observability, evals, compliance scanning.
View on GitHub - TypeScriptApache 2.0
clawlens
Agent debugging.
Session replay, cost analytics.
View on GitHub
Why you won't see a logo wall here.
A Fortune 500 logo on our site would actively reduce credibility with the operators who actually use this. Our buyers want a peer-stage reference — someone at a company like theirs, in a seat like theirs, who can tell them what actually happened. A bank logo tells a 60-person CS team nothing about whether this will work for them. It tells them we spent more time on the slide deck than the product.
The reference call.
Qualified prospects get a structured, peer-seat, on-the-record reference call with a company at comparable size and stage. Not a Fortune 500 logo drop. Someone in your seat, at a company like yours, who can tell you what actually happened — what worked, what broke, what they'd do differently.
This is how we actually close. Every qualified prospect in our pipeline has asked for it. We don't hide behind case studies. We put you on a call with someone who's done it.
What else we can show.
Anthropic's GTM use cases.
Anthropic publicly documents how Claude Code and Claude Cowork are used by GTM teams. These are the #1 referenceable proof asset — every operator we've talked to has found them more credible than any vendor case study. We'll point you to the specific ones that match your use case.
Reddit practitioner voice.
Real operators, in their own words, describing the exact pain we solve. Anonymized. Attributed to role and community. Not curated. Not polished. Just what operators actually say when no one's selling them anything.
The CSM job seems to involve stitching together a story from way too many places: usage data in one tool, tickets in another, notes in the CRM.
Sales reps don't hate logging deals — they hate switching apps mid-call to do it.
Just saw an employee pasting an entire client contract into ChatGPT.
AI tools that work great for individuals hit a wall inside enterprises.
What the data says.
Shadow AI is real and large.
- 8 in 10 employees use unauthorized AI toolsUpGuard, Nov 2025
- 93% of employees input info into AI tools without approvalManageEngine, May 2025
- ~90% of AI logins are invisible to the organizationLayerX, 2025
- 1 in 5 breaches now involve shadow AI, adding ~$670K per incidentIBM
RPA is fragile.
- 45% of firms report weekly bot breakageForrester
- 30-50% of RPA projects failEY
- A single Salesforce update can break dozens of RPA botsUiPath forum
The market is disillusioned.
- "Microsoft Scales Back AI Goals Because Almost Nobody Is Using Copilot"45,951 upvotes on Reddit
- "Peak AI Fatigue" from the Microsoft AI Tour680 upvotes on r/sysadmin
- "AI tools that work great for individuals hit a wall inside enterprises"IBM AMA, 1,986 upvotes
The pilot is the proof.
We can show you the code. We can show you the market evidence. We can put you on a call with a peer-stage reference. But the real proof is the pilot — on your systems, with your data, measured on your metrics. ~$45K. Fixed scope. Ten reps. Four weeks.