Upsolve AI: the platform to build, deploy, and evaluate grounded, governed, trustworthy data agents. Agent Context Studio is the context layer agentic analytics needs.
Hey Product Hunt 👋 I'm Ka Ling, founder of Upsolve AI.
You centralized everything in a data warehouse. You bolted an LLM on top. The demo was magic. Then it hit production and confused ARR with run rate in front of your CEO. Project shelved. You're not alone, 95% of AI data POCs never ship.
The problem was never the model. It's context. How your company defines "revenue," which table is the source of truth, the business rules that live in someone's head and a dbt file from 2021. Models can't guess that. a16z and OpenAI both said the same thing this year.
Upsolve AI is the context infrastructure for analytics agents. We encode your institutional knowledge across three layers: Structure (schemas, lineage), Meaning (your metrics + rules), and Trust (verified answers, evals, full observability).
Two sides, one platform:
Agent Studio: data teams encode, test, and tune agents that reason like your best analyst. 1 day, not 6 months.
Agentic Dashboard: anyone asks questions in plain English. No SQL, no queue, no 3-day wait.
Deploy the same agent everywhere your team already works, Slack, Teams, your own product, or Claude.
Already live with Fortune 500s, 60+ person BI teams, and growth-stage companies like Effi, Skylink, and Arthur AI.
What's broken about data and analytics agents in your world? I'm here all day. 🙏
Report
What's the biggest thing you've learned about how people actually interact with AI analysts that you couldn't have discovered without shipping to real customers?
@harshchandgotia we have an internal evaluator called User Frustration. It gets triggered when a similar question is asked in the same session multiple times. It's one of our best way to understand what is the new feature to build because if that gets triggered, it means people persistently want it to work.
@thamibenjelloun Yeah! We support both data-level permissions (RLS, CLS, etc) for your users, as well as role-level permissions (admin, editor, read-only, etc) with full customization for both
Report
Strong framing. The hard part with analytics agents is usually not the chart, it is what happens after the answer gets trusted. If someone turns an insight into a report, Slack update, or downstream task, do you keep that action trail in the same context layer or outside it?
Replies
Upsolve AI
Upsolve AI
@harshchandgotia we have an internal evaluator called User Frustration. It gets triggered when a similar question is asked in the same session multiple times. It's one of our best way to understand what is the new feature to build because if that gets triggered, it means people persistently want it to work.
Mailwarm
Can you set different permission levels so some users can ask questions but not trigger write actions?
Upsolve AI
@thamibenjelloun Yeah! We support both data-level permissions (RLS, CLS, etc) for your users, as well as role-level permissions (admin, editor, read-only, etc) with full customization for both
Strong framing. The hard part with analytics agents is usually not the chart, it is what happens after the answer gets trusted. If someone turns an insight into a report, Slack update, or downstream task, do you keep that action trail in the same context layer or outside it?
Upsolve AI
@blah_mad If they do them with Upsolve's ecosystem (e.g., if they share the insight as an upsolve canvas), then we are able to trace that.