Sep 19, 2026 · 6 min read
What is a queryable company?
Y Combinator says the best AI-native companies have made their entire company queryable. Here is what that means, why it is hard today, and how to start.
What is a queryable company?
A queryable company is one where the work itself is captured and connected, so a person or an AI agent can ask a question about the business and get an answer grounded in what actually happened. Meetings are recorded, tickets are tracked, customer conversations are captured, and decisions are written down, all in a form an intelligence layer can read, reason across, and learn from.
Y Combinator has popularized the term in its 2026 material on AI-native companies. It describes a property of the whole company, not a single tool. A company is queryable when you can ask “why did we build this?”, “what are customers asking for this month?”, or “did last quarter’s launch work?” and get an answer that links back to the evidence.
What does Y Combinator mean by a queryable company?
YC uses the term to describe what separates the best AI-native companies from the rest. In the Summer 2026 Requests for Startups, YC Partner Diana Hu wrote that the best AI-native companies “have figured out something most haven’t: they’ve made their entire company queryable.” She described it as “Every meeting recorded, every ticket tracked, every customer interaction captured, all legible to an intelligence layer that learns from it.”
Her argument is that this changes how a company runs. In her words, it “turns a company from an open loop into a closed loop.” In an open loop, you make a decision and maybe check the results weeks later. In a closed loop, the system monitors what is happening, compares it to what should be happening, and adjusts.
Hu made the same case in her Startup School talk on building an AI-native company, where she described the goal as a company that is “queryable, artifact rich, and legible to an AI.” The principle underneath is simple: “you need to provide models with as much context as you would provide an employee.”
YC applies this to itself. On the Lightcone podcast, YC General Partner Pete Koomen said the first step is to “start recording all the artifacts. It’s like a shared organizational brain,” and that building YC’s own agents showed him “there’s a lot of value, at least, in getting all of the context into one place.”
What does a queryable company capture?
A queryable company captures the artifacts where decisions are actually made and tested. For most software companies, that means five kinds of context:
• Conversations: customer calls, sales calls, internal meetings, and in-person discussions, recorded and transcribed with consent.
• Work in progress: tickets, pull requests, specs, and roadmaps in tools like Linear, Jira, GitHub, and Notion.
• Communication: Slack threads and channels, with decisions moved out of private DMs.
• Customer signals: support tickets, feedback, and usage data from product analytics.
• Decisions and outcomes: what was decided, why, what was expected to happen, and what actually happened after release.
The last category is the one most companies miss. Capturing activity without capturing decisions and results gives you a searchable archive, not a closed loop.
Why is it hard to make a company queryable today?
Because the context lives in a dozen disconnected tools, and connecting them takes custom engineering most teams do not have time for. YC says this directly: building this today “requires brutal integration work, stitching together Slack, Linear, GitHub, Notion, call recordings, and a dozen other tools with custom glue code.”
Even when the data is collected, three problems remain:
• Nothing reasons across sources. A complaint in a call, a spike in support tickets, and a drop in a metric may describe the same problem, but they sit in different systems.
• Evidence gets separated from decisions. Tickets rarely link back to the conversations that justified them, so no one can later check whether the work matched what customers said.
• Outcomes are not fed back. Teams ship and move on, so the loop stays open.
YC’s request names the missing piece as a product that “connects all this context into a single intelligence layer that can reason across it, flag when engineering is building the wrong thing, or generate specs agents can execute on.”
Is a queryable company the same as a data warehouse or a search tool?
No. A data warehouse makes structured metrics queryable, and enterprise search makes documents findable. A queryable company goes further: it connects unstructured context such as conversations and decisions with structured data such as tickets and metrics, and it keeps the links between them, so the system can explain why something happened and whether a decision worked.
Hu describes the goal as “Not another dashboard.” The difference is reasoning and feedback: the intelligence layer does not just store context, it uses it to flag problems, draft work, and learn from outcomes.
How do you make your company queryable?
Start with one important process, capture everything that feeds it, and connect it to outcomes. You do not need to rebuild the company at once.
1. Pick one loop that matters, such as product planning, onboarding, or customer support.
2. Record the conversations that feed it, including customer calls and internal meetings, and tell people you are recording.
3. Move decisions into shared channels and docs instead of DMs.
4. Connect the systems where the work lives: your notetaker, Slack, your issue tracker, your docs, and your analytics.
5. Link each decision and ticket to the evidence behind it.
6. Write down the expected impact of every meaningful decision, then compare it with actual results after release.
7. Feed what you learn into the next decision, then repeat the pattern for the next process.
We cover the broader operating model in our guide to how to build an AI-native company, and the feedback step in what closed-loop product management is.
Where Fijord fits
Fijord is a product-management platform, in early access, that makes product work queryable. It connects the tools teams already use, including meeting notetakers and recordings (Granola, Gong, Zoom, Google Meet), Slack, Linear, Jira, Notion, GitHub and Mixpanel, and builds one shared product memory from calls, docs, tickets and metrics. Transcripts from other sources, including in-person recorders, can be added as manual inputs.
From there, you can ask questions about your product and get answers with sources. Signals surface as evidence builds on a topic, Pulse flags blockers, approvals, risks and opportunities, and Fijord drafts briefs, epics and tickets from the evidence and syncs them to Jira or Linear. Each recommendation carries a predicted impact, and after release Fijord compares it with actual results in your analytics, so the next decision starts from what actually happened.
Frequently asked questions
Where does the term “queryable company” come from?
Y Combinator has used it throughout its 2026 material on AI-native companies, including Diana Hu’s Startup School talk and YC’s Summer 2026 Requests for Startups.
Does a queryable company need to record every meeting?
It needs to capture the conversations that feed important decisions. Record with consent, and check the recording laws where you and the other participants are located.
What is the difference between a queryable company and an AI-native company?
Being queryable is a prerequisite. An AI-native company uses that queryable context to run closed loops, where agents and people act on the evidence and learn from the results.
Can a small startup be queryable?
Yes, and it is easier early on. Small teams have fewer tools, fewer habits to change, and no legacy systems to unwind.
What tools make a product team queryable?
A meeting notetaker, a shared messaging workspace, an issue tracker, a docs tool, and product analytics, plus a layer that connects them. Fijord is built to be that layer for product work.