Data Panda brings your Guru cards, collections and verification workflow together with the rest of your business systems. From one place, we turn your knowledge base into dashboards, automations, AI workflows and custom apps the people answering customers use.
Guru was founded in 2013 in Philadelphia by Rick Nucci and Mitchell Stewart, both formerly at Boomi where Rick was a co-founder and CTO before the Dell acquisition in 2010. Headquarters remain at Independence Mall in central Philadelphia.
Where Notion and Confluence keep growing as long pages of mixed quality, Guru is shaped around a smaller atomic unit: the card. Every card has a designated verifier, a verification interval and a trust state. When the clock runs out, the card flags itself for review. On top of that base, Guru has shipped Knowledge Agents and an AI Search layer that answers employee and customer questions across Slack, Teams and the browser, with a citation back to the card and a permission check on the user. The bet is that an LLM is only as accurate as the knowledge it was given, and a verified card is the only knowledge worth quoting.
Verified versus overdue cards, verifier load, search hits and misses across every collection.
Let Guru events drive the rest of the stack instead of nudging colleagues over Slack to verify their cards.
Ground your own AI in cards that have a verifier and a freshness date, not the whole intranet.
Small tools for verifiers, collection owners and the people running the knowledge program.
A list of concrete reports, automations and AI features we have built on Guru data. Pick the one that matches your situation.
How much of our knowledge base is trusted right now?
Cards split into verified, overdue, never-verified and trust-broken, per collection and verifier. Trended over time so you can see whether the verification discipline is improving or quietly slipping. That number, not the total card count, is what tells you whether AI Search is allowed to cite from a given collection.
Which questions does our team keep asking that no Guru card answers?
Internal search queries with no result or no click, joined to support ticket subjects and Slack help-channel threads. Ranked by frequency and by the cost of the people who keep typing them. That is the actual prompt list for the next round of card writing, not a guess in a planning meeting.
Are our AI answers grounded in cards we trust?
Each AI Search answer is matched to the cards it cited and the verification state of those cards at the time of the answer. Surfaces the share of answers grounded in overdue or unverified cards, per assistant and per question topic. The fix is rarely the LLM, it is the source it pulled from.
When Guru carries policy cards, expense rules and vendor procedures, finance gets a read on which policies are verified, which are overdue, and how often staff search for one and click away. Audit prep stops being a scramble for proof that the policy was current on the day someone followed it.
Sales enablement gets a real read on which Guru cards reps open during a deal, which they ignore, and which questions from prospects come back to the same gap. Battlecards stop being a vanity asset and become a measurable one.
A live picture of the knowledge base instead of a quarterly clean-up panic. Operations sees overdue verifications, verifier load and which collections are growing without owners, and can rebalance the program before it tips over.
Overdue Guru cards trigger a compact reminder to the verifier in Slack, posted to a channel the team reads, with a one-click link to verify or update the card. Verification stops being an email someone ignores and becomes a visible team metric. A weekly digest in the same channel shows the verifier league table and the cards still red.
When a Guru card behind a customer-facing macro or article is updated and re-verified, the matching Intercom content updates with the same wording. Support stops reading from a stale macro while the internal card already moved on, and the help center, the saved replies and the source card converge on a single published version.
When a Salesforce opportunity is at a competitive or pricing stage, the matching Guru battlecards and verified pricing cards are linked on the record, scoped to the rep's permissions. Reps stop searching two tools and the enablement team gets back which cards were opened on which deals, by stage, against win rate.
Recurring questions from prospects, captured in HubSpot conversations or contact properties, are matched to internal Guru search misses. When the same question hits a fixed threshold, a task lands on the marketing or product-marketing queue in HubSpot to write or update the card. The knowledge gap stops being anecdotal.
Cards past their verification date land as items on a monday.com board, grouped by collection and verifier, with the original Guru link and the days overdue. Heads of department can run knowledge maintenance like any other backlog instead of nagging individuals one by one in chat.
When a long-form Notion page reaches a defined status (Published or Final), the canonical short version is created or updated as a Guru card with the verifier and collection set on the Notion side. Notion stays the drafting and discussion space, Guru stays the place support and sales quote from, and the two stop drifting.
You keep the reporting tool you already have. We connect it to the warehouse where your Guru data lives.
OAuth authentication. Read-only by default. We sign a DPA and your admin keeps the keys.
Data flows into your warehouse on your schedule. Near real time or nightly, your call. You own the data.
We build the first dashboard, workflow or AI feature with you, then hand over the keys. Or we stay on for ongoing delivery.
We set up the foundation. Your team builds on top.
Best fit Teams that already have a BI analyst or data engineer and want to own the build.
We build the whole thing, end to end.
Best fit Teams without in-house BI or dev capacity. You tell us what you need and we deliver it.
You do. It lands in your warehouse, on your cloud account. We don't resell or aggregate it. If you stop working with us, the warehouse stays yours and keeps running.
Near real time for most operational systems. For heavier sources we schedule hourly or nightly. You pick based on what the reports need.
No. If you don't have one, we help you pick one and set it up as part of the first delivery. Common starting points are Snowflake, Microsoft Fabric, or a small Postgres start.
Each card carries its verification state, the named verifier, the verification interval and the last-verified timestamp. We land those as columns alongside the card itself, so you can compute overdue, time-since-last-review and verifier load directly in SQL. The verification state at the time of an event (an AI answer, a search hit) is what we keep, so you can audit retrospectively which cards were trusted on the day they were quoted.
Cards are the atomic content unit, each with a verifier and a trust state. Collections are the top-level container, usually owned by a team. Folders sit inside collections and group related cards for navigation. Older boards still exist on some accounts. We model cards as the fact and collections, folders and boards as dimensions, so you can pivot the same card view by team, by topic and by ownership without rebuilding the tables.
Where Guru exposes the data, yes. AI answers, the cards they cited and the user query come across, which is what makes coverage and grounding analysis possible at all. Some Knowledge Agent telemetry is only surfaced in the Guru admin UI; we mirror what the API returns and call out the gaps explicitly rather than inventing numbers.
We review your Guru setup and the systems around it. Together we pick the first thing worth building.