View the full benchmark → textql.com/decision-bench

Muse Wonder achieves 34.0% on Decision-Bench, our frontier benchmark for data-driven decision making. It improves substantially from Muse Spark’s 19.8%, but at over 2x the cost: Wonder uses fewer output tokens, but each one costs 3x more.

Read more 👉 textql.com/blog/ontology-ga?…

TextQL’s Ontology is now generally available. Business context and executable logic, together in files agents can read and use, and your team can review, version, and own. Business as code, built for the way agents work.

Read more: textql.com/blog/dropbox-conn…

Dropbox is now connected to Ana. Ana can read the contents of your PDFs, docs, spreadsheets, and Paper docs — not just search filenames. Ask questions across Dropbox and your other connected data sources in one place. Available today to all TextQL customers.

Read more: textql.com/blog/fable-5-1-an…

Fable 5.1 is now live in Ana. Faster. Stronger on coding. Up to 45% cheaper on agentic workloads. That means deeper investigations and long-running agents in Ana just got faster and significantly cheaper to run at scale. Select Fable 5.1 from the model picker.

♠️ TextQL is growing our engineering team, and we'd rather meet you over cards than over a whiteboard. We're hosting a friendly poker night on Wednesday, August 26 in our new NYC office. All experience levels welcome. RSVP in comments ↓

[redacted]

"us" lol

Read more: textql.com/blog/5-data-apps?…

Yesterday, we launched Data Apps to all customers. Today, Aaron Zhu walks you through how to build a working Data App from a single prompt. He shows how to build a data reconciliation workflow: a leasing intake portal that takes messy broker reports and uses an agent to validate them. The agent surfaces anomalies, brings in human input where needed, and writes clean, validated rows back to the warehouse. This is just one example. In the blog post below, we're rounding up a few more data apps that impressed us, for inspiration.

Read more: textql.com/blog/data-apps-la…

Meet Data Apps. We took what makes low-code and no-code app builders great: speed, no engineering bottleneck. And applied it directly to enterprise data. The result: fully operational apps built in one or two prompts. Accurate. And fully enterprise-ready out of the box, with version control and RBAC built in, not bolted on afterwards. We're offering free credits to Team and Enterprise organizations building their first three data apps. Try it today by describing what you want to build in a new chat. That's it. Learn more about customer examples in our blog post below 👇

Claude Opus 5 is now available in TextQL. To turn it on for your organization, head to Settings > Models and toggle Enabled next to Claude Opus 5.

🎙️ Watch the full podcast: youtu.be/PwhlxJrjQgQ?si=NdEP…

Enterprise data teams are still running modern data stacks like 1910s Detroit assembly lines. @TheEthanDing, CEO, sat down with @petesoder of @ZeroPrimeVC to talk about why that model is breaking now, and what TextQL does differently: working directly on messy enterprise data instead of demanding clean inputs first. The dirtier the data, the more this approach pays off. And because TextQL builds context over time, it gets cheaper with use instead of more expensive. They also covered the question every data leader is quietly panicking about: AI is spiking warehouse bills exponentially. The old playbook does not survive contact with that math. Thanks to Pete and the Zero Prime Ventures team for having us.