Enterprise AI has a context problem. Together, we’re taking on the hardest part: capturing how a company works and keeping that knowledge current.
A model can read every policy, contract, and decision a company has on file. It still does not know why a decision was made, when a rule stops applying, or what changed after the document was written.
Much of what matters is trapped in people’s heads or spread across systems, conversations, workflows, and years of operating history. The hard part is capturing that context, preserving its source and permissions, and keeping it current as the business changes.
With the right context, agents can take on core workflows. Without it, they stay limited to narrow tasks and human workarounds.
Tribe exists to help enterprises take bigger swings with AI. Context is what makes those swings possible.
We see this problem in the enterprise workflows we rebuild. Our Forward Deployed engineers sit alongside the experts whose judgment those systems need. We make product decisions together, handle exceptions, and learn from production.
We’re building ways to capture that judgment as work happens: observing decisions, asking experts why they made them, and turning those answers into context agents can use. The harder problem is closing the loop. When an expert corrects an agent, that feedback should improve the system instead of disappearing into a spreadsheet.
Most enterprise AI work gets rebuilt from scratch every time: same discovery, same false starts, same knowledge lost when the engagement ends. We’ve turned that into a discipline instead, a way of working that compounds instead of resetting each time. What we learn on one engagement makes the next one faster.
When we met the HipAI team, the fit was obvious. Led by co-founder and CEO Boris Revechkis, they had been working on another part of the same problem: organizing and surfacing context through document-heavy legal work, where a single matter could span hundreds of thousands of documents.
They built connectors and ontologies, worked on graph-based retrieval and context distillation, and learned where these systems break in practice.
“We went deep on this problem in legal. Tribe was seeing it across some of the world’s largest enterprises. Joining the team gives us the chance to take what we learned and tackle it at a much larger scale.” — Boris
We believe context is core to our customers’ success with AI. We’re going all in and bringing the right people with us.
And yes, we’re hiring.
Co-Founder & CEO
Jackie spent the majority of her career at Google partnering with enterprise companies and incubating new products. She was an early employee at CapitalG, Alphabet’s growth equity firm, where she built a fifty-thousand-person expert network and advised growth-stage tech companies like Airbnb on scaling their technical infrastructure, data security, and leveraging machine learning for growth.
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