Upsolve AI provides a two‑sided platform that lets developers build observable, context‑aware analytics agents and lets end users query their data via natural‑language chat. The agents connect to 30+ SQL warehouses, import dbt projects, and use encoded institutional knowledge to generate KPI‑verified SQL results with full data lineage, delivering trusted visual insights on demand.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Data teams spend extensive time manually integrating disparate data sources, encoding business rules, and building custom analytics interfaces, leading to slow insight delivery and low user trust in AI-generated answers.
Solution
Upsolve AI offers a two‑sided platform that lets developers create observable, context‑aware analytics agents and enables end users to query their data via natural language chat without leaving their product. The platform connects to 30+ SQL warehouses and can import existing dbt projects, while its context infrastructure encodes institutional knowledge such as KPI definitions and business rules. Agents generate SQL, fetch results, and return verified answers with full data lineage, improving accuracy and trust. Built‑in observability, credit‑based usage, and optional enterprise features (RBAC, embedding, on‑prem deployment) allow organizations to scale AI‑driven analytics securely.
Target Audience
Primary customers are product and data teams at SaaS, fintech, and enterprise software companies that need to embed trustworthy, AI‑driven analytics directly into their applications.
Features
- 30+ out‑of‑the‑box connectors to major warehouses (Snowflake, BigQuery, Redshift, Postgres, Databricks, MySQL, etc.) and optional dbt project import
- Context management suite that encodes KPI definitions, metric semantics, and institutional knowledge to produce KPI‑verified answers
- Unlimited analytics agents with full observability, including query lineage from source to model to answer
- Visual insights and chart generation delivered through an embeddable frontend or web dashboard
- Credit‑based pricing model that charges per AI interaction, with simple queries using 1‑3 credits and complex analyses up to 20 credits
- Enterprise controls: row‑level security/RBAC, SAML SSO, HIPAA/SOC 2 compliance, VPC/on‑prem deployment, and BYOM (bring‑your‑own‑model) support
- Forward‑deployed engineering assistance for semantic layer creation and context engineering in custom contracts