Sentra: The Operational Nervous System

Scaling breaks organizations in predictable ways. At 20 people, you lose the ability to sync over lunch. At 50, product-engineering alignment fractures. At 150, cross-functional context evaporates. At 500, executives are governing a company they no longer understand. Companies scaled by adding processes to compensate. More standups. More status docs. More dashboards. Each layer added friction while reducing actual understanding. Notion pages went stale within weeks. Confluence became a graveyard. The result: organizations tracked everything about what happened and understood nothing about why.

The future belongs to companies where AI deeply understands the business, not as a search engine over stale documents, but as a living participant in how work actually happens. Memory is not an archive. Archives store dead artifacts waiting to be searched. A company with 10TB of Google Drive isn't knowledgeable. It's hoarding. Memory understands. It connects. It learns continuously. A library holds books. A scholar reads them, connects ideas across volumes, and develops judgment over time. What we call "institutional memory" today is actually institutional amnesia with good filing.

Today we rely on fragmented SaaS tools that require constant manual feeding. We serve these tools. We update tickets. We log calls. The tools don't serve us; they demand tribute. Sentra builds memory that eliminates the need for tribute entirely. This was impossible until very recently.

Why wasn't this built before? Because until now, AI was retrieval, not reasoning. It could find a file. It couldn't understand a company. Three thresholds changed that. First, the digitization of dark matter: spoken decisions, hallway negotiations, ad-hoc brainstorms used to evaporate the moment they happened, that friction has collapsed. Second, context windows exploded from 4K to over 1M tokens, so we can reason over organizational history, not just search it. Third, continuous memory revision: Sentra maintains a living state of your organization that updates as decisions occur, without model retraining.

Borrowing from Kahneman: organizational thinking happens in two modes. System-2 is structured output, Jira tickets, PRDs, quarterly reports. System-1 is raw cognition, the negotiation of reality in meetings and conversations where decisions actually get made. Most tools only capture System-2. But System-2 is derivative. By the time something becomes a ticket, the actual thinking has already happened elsewhere. Sentra captures System-1 directly, building genuine understanding of how decisions are made, how projects evolve, and how context flows through your company.

When AI weaves System-1 and System-2 together across an entire company, something new emerges. Call it System 3: collective intelligence at the organizational level. The organization doesn't just store its thinking. It actually thinks, as a coherent entity, not just individuals trying to stay aligned. Single-player AI optimizes one person's workflow. System 3 is multiplayer cognition.

What does this look like? An engineer asks why the architecture looks this way and gets the full decision history immediately, no coffee chats, no archaeology through old PRDs. A VP joins; within a week, they ask Sentra why the Q3 pricing decision was made, who disagreed, and what changed since, context that used to take six months of hallway conversations. A founder wakes up Monday and gets a single synthesis across engineering, sales, and ops, not status docs to reconcile, but a coherent narrative with risks surfaced. A COO notices drift; instead of four meetings to triangulate, they get the full decision history, blockers, and who needs to be in the room. The coordination tax flattens. Process becomes optional.

Today's AI agents are impressive but fundamentally single-player. Claude Code, Copilot, Operator, they excel at tasks one person can describe to one computer. They don't understand organizations. The problem we're solving isn't "how do I automate my individual work." It's "how do I keep fifty people aligned when context fragments across hundreds of conversations daily." Glean searches documents. Copilot summarizes what's in front of you. Neither builds memory. Neither connects a March conversation to a June decision to a September consequence. Why can't they? Because this is a research problem.

Making coherent sense of millions of tokens of organizational context requires new science. We built Reflexion at MIT (NeurIPS 2023). Now we're extending it into Operational Reinforcement: by maintaining short-term memory of errors as they form, we enable real-time correction that dramatically improves performance. We've shown that 4-billion parameter models fine-tuned with this approach match GPT-3.5 and GPT-4o on coding benchmarks. We're extending these capabilities to increase context length, improve temporal reasoning, and model how decisions propagate through organizations.

Our moat deepens with time. Every month Sentra operates inside a company, it becomes harder to replace. The learned context of how this specific organization communicates isn't exportable. OpenAI starting fresh in 2027 has zero historical context for your company.

If Sentra is ingesting every meeting and every chat, you're right to ask: who else can see this? Your memory stays yours alone. Your organizational memory is entirely isolated, your strategy meeting can't leak into another customer's context. Your data never trains a shared model. You control retention. Access mirrors your org structure: an IC can't query executive discussions. We earn trust through architecture, not promises.

There's a missing layer that actually runs enterprises: the decision traces. The exceptions, overrides, precedents, and reasoning that currently live in Slack threads and people's heads. A VP approves a discount over Zoom. A support lead escalates based on synthesis across three systems. The reasoning connecting data to action was never treated as data. When Sentra captures this, precedent becomes searchable. One-off exceptions turn into institutional knowledge. OKRs reflect what's actually happening. Project status updates itself. The engineer who quietly unblocks three teams is finally seen. CRM entries populate from conversations. When someone asks "why did we do it this way?", there's an answer, not a guess, but the actual decision trace.

Over time, patterns will emerge across companies. Not shared data, but shared learnings. A founder could understand how similar decisions played out at companies like theirs, while every company's memory stays isolated. No more tribute. The tools finally serve you. Where founders stay in founder mode at two hundred people, not because they sit in every meeting, but because they have an agent that does, and actually understands what it hears.

Sentra. Memory that learns.