TextQL

95% of Healthcare data lives in petabytes of SQL databases The tools for AI to use that data haven't existed Today we fix that with TextQL Healthcare 100,000+ tables. Trillions of rows. Petabytes of data. 15 minutes to insights. Epic systems with 100,000+ tables. Cerner environments. Claims databases. Clinical notes. Prior authorizations. Healthcare organizations have more data complexity than any other industry - and exactly zero AI platforms built to handle it. Until now. Here's what makes it different: 1. Direct access to ALL your systems. No migration required. Epic + Cerner + Claims + Snowflake + Databricks. Everything. At once. Other platforms: 6-month ETL projects. TextQL: Connect Monday. Query Tuesday. First insights in 15 minutes. 2. Healthcare-compliant execution environment. Autonomous agents running production code in SOC 2 Type II, HIPAA-compliant infrastructure. Full audit trails. On-premise deployment available. 3. Structured AND unstructured data. Simultaneously. Everyone else: Claims records OR clinical notes. Us: Both. At the same time. Make sense of 100,000s of tables without months of data prep. We're not launching with pilots. We're launching with Lumeris - powering their Tom™ AI platform delivering care to millions of Americans. Live partnership. Production workloads. Enterprise healthcare data at scale. Advisory Board of operators who've run organizations serving 120M+ Americans: - Varsha Rao (former CEO Nurx, COO Clover Health) - David Griffith (Trinity Life Sciences, ex-Pfizer) - Sam Mohanty (former CDO, Prime Therapeutics) - Jean-Claude Saghbini (CTO, Lumeris) - Raghu Chandra (30 year EHR Veteran) These aren't advisors. They're the people who built the systems we're now optimizing. Meet us at HLTH Conference next week - Booth #4060 Or request a demo: textql.com/hlth-conference Comment "HEALTHCARE" and we'll reach out for a customized demo!

Seat-based SaaS stocks are tanking. Wall Street is scared. We decided to speed it up. Introducing $0/ Seat Dashboards by TextQL $0/viewer seats $0/editor seats $0/admin seats Unlimited seats. Forever. Our agents build dashboards directly on your Datawarehouses, APIs, MCPS. Even on top of Tableau and Power BI. Dashboards have always been built. From now on, they're generated. Build a dashboard and get $100 in credits Link below:

true, might as well just say the quiet part out loud

🚨BREAKING🚨 Zohran Mamdani will FORCE all NYC companies to fire any consultant charging $500/hr to build a data strategy deck. "To build a city in which all New Yorkers can thrive, we cannot allow McKinsey to sell us 47 slides that say 'become data-driven.'"

Most teams: Paying for Snowflake but only 3 people can query it TextQL: 3-minute setup, entire team gets self-service access New tutorial covers key-pair auth, schema mapping, the whole thing. Connect once. Ask questions forever. Link below.

Most teams: 3 days to write SQL queries for basic insights TextQL + PostgreSQL: 3 minutes New tutorial shows the setup. Neon, Supabase, AWS RDS—doesn't matter. Connect once. Ask questions forever. Link below.

We're throwing a happy hour during #JPM2026. Monday, Jan 12. 5:30pm. Neo Office, SF. Enterprise data and AI folks—come talk shop over drinks. No pitch decks allowed. Link Below.

santa came early: TextQL compute is now 80% cheaper turns out when AI agents query your warehouse 10x more someone has to pay for it. we decided it shouldn't be you two updates shipped this week:sandcastle lifecycles down to 4 hours → 80% lower sandbox costs token cache hit rate up from 40% to 52% → 17% lower token costs net result: 30%+ reduction in total costs for most customers our job is to drive the cost of data-driven decisions toward zero. every price cut is a feature

@FixedIncQuant just think of a computer your agent can use to accomplish more complex tasks. ex, writing python, storing the output in s3 and returning the blob to the user

@TextQL What exactly does sandbox mean in this context ?

Most AI sandboxes are built to run code We needed one built to wrestle with petabytes of enterprise data across dozens of sources. Here's what we learned building Sandcastles (1/7)

@IbrahimGaz03 not as based as you

basedscalemaxxing

@sydnytrn goated sydney

goated team 🐐

Checkout The Full Engineer Blog: textql.com/blog/sandcastl…

7. What's next. Collapsing the query engine into the sandbox (60% latency reduction estimates). Persistent sandboxes that become live applications instead of spinning down. Fine-grained network permissions so agents can call external APIs without binary "isolated vs connected" tradeoffs. (7/7)