Collect — automatically
Issue trackers, code repositories, email, team chat, meeting recordings, AI work sessions, documents — pulled in on a schedule, no manual import, no “please update the wiki”.
Proven in production — not promises
Every company's real knowledge is scattered across tickets, code, email, chat, meetings and people's heads. LStairs gathers it into one living memory — and puts an AI agent on top of it that can know your company better than any single expert inside it.
The moment of truth
Someone asks the AI agent: “bring up the test server.” Without company memory, that's a scavenger hunt across accounts, records and “who remembers the password?”. With memory, the whole chain is already inside the system.
the right account, machine and network records — in company memory, not in someone's head.
started the server and noticed its address had changed after the restart.
corrected the records, verified every service was back and reachable.
wrote the lesson back into memory — so next time is even faster.
This is not a demo script. This is production memory that already works — as if every employee had an experienced assistant, and all the assistants shared one brain.
The cost of inaction
Senior hours burned on “who knows this?”. Onboarding from zero. AI tools that don't know your history. Decisions already made — and forgotten. Context that walks out the door when a key person leaves.
Every month of waiting grows this bill.
Import years of history and see a business picture in weeks — one no single tool holds. Then every working day strengthens the asset. AI and people rely on the same facts. Experience stays in the company.
Ownership of knowledge — instead of hoping “we'll document it somehow”.
What we build
We're not selling a chat or a wiki. We're selling a vessel: memory infrastructure. It fills itself from the systems your teams already use — and becomes an asset no vendor can sell you, because it's made of your own experience, decisions and processes.
Issue trackers, code repositories, email, team chat, meeting recordings, AI work sessions, documents — pulled in on a schedule, no manual import, no “please update the wiki”.
The platform links tasks, people, code, discussions and decisions into one graph — and distills them into higher-level knowledge: rules, conclusions, trends.
People search by meaning or keyword in one window. AI agents tap the same memory natively, mid-task, through an open standard — before they answer, they read; they don't invent.
Every ticket closed, commit made and meeting held makes the memory smarter — and agents write their own lessons back. The longer it runs, the harder it is to live without.
Why we're different
| What companies try | Where it falls short | LStairs |
|---|---|---|
| General AI chat | Doesn't know your history, decisions or code | Memory built from your real work |
| Wiki / documentation | Goes stale — nobody updates it | Updates itself, continuously |
| A folder of documents | No links between task, code and decision | A connected knowledge graph |
| Enterprise search SaaS | Your knowledge on someone else's servers | Self-hosted — your asset, your moat |
Most AI products sell “hands without a brain” — smart chat with no history. We sell the brain: agents and automations read it, act, and put what they learned back. Action without losing experience.
AI models turn over every few months. Your knowledge, decisions and conclusions live in your vessel; models plug in as swappable lenses. If a vendor disappears, your memory doesn't.
Memory is layered by day, week, month, quarter. “What changed this spring?” gets a narrative grounded in facts — for leadership, for agents, even for due diligence.
The codebase itself is indexed as memory — what it does and why it's this way. An engineer and an AI agent onboard from the same product map. You can't buy that by installing a chatbot.
The same memory answers a new hire's question and powers an agent's next action. No parallel silos, no stale copies — one source of truth for humans and machines alike.
Run it in our cloud, your cloud, or a fully offline perimeter with local AI models. For companies whose knowledge is the business, that isn't a feature — it's the deciding factor.
Who benefits
Reads “how we do things here”, sees decision history, ramps in days.
Weeks of onboarding savedSees open work, load and discussions without polling the team.
Fewer status meetings“Why did we choose this architecture?” — answered with date, author and context.
Fewer costly rollbacksFinds past similar failures, fixes and discussions — never starts from zero.
Hours saved per incidentKnows your stack, past decisions and constraints before it writes a line.
A multiplier, not a toyAuto-reports and history on demand — a data-driven narrative, not a quarterly scramble.
Visibility without spreadsheetsWhere we are
Deployed and running around the clock: ingest on schedule, updates without downtime, memory that doesn't go stale by itself.
Teams already ask it the questions they used to ask their most senior people — and get answers grounded in their own history.
Foundation, enterprise-grade storage, automation, live email and meetings — shipped at high velocity by a compact team.
Honestly: quality on the hardest search queries is the team's current focus. The architecture is ready; the polish is measured by benchmarks, not gut feel. We'd rather show you that than hide it.
The vision
No single cloud knows everything about your company — each vendor holds one fragment and shares nothing. The full picture exists only in your people's heads, until it leaves with them. We're building the layer that captures it, compounds it, and hands it to every person and every agent — one step at a time.
For investors
A working product, real users, a market that every AI adoption curve points straight at — and a team that has already built what others are still pitching. If you invest in the infrastructure of the AI era, we should talk.
We reply personally, usually within a day.