VentureBeat Mar 31, 02:28 PM
Imagine if your Teams or Slack messages automatically turned into secure context for your AI agents — PromptQL built it For the modern enterprise, the digital workspace risks descending into "coordination theater," in which teams spend more time discussing work than executing it.
While traditional tools like Slack or Teams excel at rapid communication, they have structurally failed to serve as a reliable foundation for AI agents, such that a Hacker News thread went viral in February 2026 calling upon OpenAI to build its own version of Slack to help empower AI agents, amassing 327 comments.
That's because agents often lack the real-time context and secure data access required to be truly useful, often resulting in "hallucinations" or repetitive re-explaining of codebase conventions.
PromptQL, a spin-off from the GraphQL unicorn Hasura, is addressing this by pivoting from an AI data tool into a comprehensive, AI-native workspace designed to turn casual, regular team interactions into a persistent, secure memory for agentic workflows — ensuring these conversations are not simply left by the wayside or that users and agents have to try and find them again later, but rather, distilled and stored as actionable, proprietary data in an organized format — an internal wiki — that the company can rely on going forward, forever, approved and edited manually as needed.
Imagine two colleagues messaging about a bug that needs to be fixed — instead of manually assigning it to an engineer or agent, your messaging platform automatically tags it, assigns it and documents it all in the wiki with one click Now do this for every issue or topic of discussion that takes place in your enterprise, and you'll have an idea of what PromptQL is attempting. The idea is a simple but powerful one: turning the conversation that necessarily precedes work into an actual assignment that is automatically started by your own messaging system.
“We don’t have conversations about work anymore," CEO Tanmai Gopal said in a recent video call interview with VentureBeat. "You actually have conversations that do the work.”
Originally positioned as an AI data analyst, the company—a spin-off from the GraphQL unicorn Hasura—is pivoting into a full-scale AI-native workspace.
It isn't just "Slack with a chatbot"; it is a fundamental re-architecting of how teams interact with their data, their tools, and each other.
“PromptQL is this workhorse in the background, this 24/7 intern that’s continuously cranking out the actual work—looking at code, confirming hypotheses, going to multiple places, actually doing the work," Gopal said.
Technology: messages that automatically turn into a shared, continuously updated context engine
The technical soul of PromptQL is its Shared Wiki. Traditional LLMs suffer from a "memory" problem; they forget previous interactions or hallucinate based on outdated training data.
PromptQL solves this by capturing "shared context" as teams work. When an engineer fixes a bug or a marketer defines a "recycled lead," they aren't just typing into a void. They are teaching a living, internal W