WisdomAI
by Wisdom AI Inc.
Agentic analytics platform and AI data analyst that answers business questions across warehouses, documents and SaaS tools
WisdomAI is an agentic analytics platform for enterprise data and business teams. Its AI data analyst answers plain-English questions across warehouses, documents and business tools, and proactive agents watch KPIs and explain anomalies, which takes routine ad-hoc requests off the data team's queue.
WisdomAI is an enterprise analytics startup led by CEO Soham Mazumdar, a co-founder of Rubrik who left that company in 2023; his co-founders Sharvanath Pathak (CTO), Kapil Chhabra (CPO) and Guilherme Menezes (Chief Architect) also worked with him at Rubrik. The company launched formally in late 2024, raised a $23M seed led by Coatue in May 2025 and a $50M Series A led by Kleiner Perkins with NVentures in November 2025, about $73M in total. Its design choice for accuracy is that the language model writes the query sent to the data warehouse and never writes the answer itself, so a hallucination produces a failed query rather than an invented number. An Enterprise Context Layer learns each customer's schemas, metrics and business terms and updates from user feedback, and an Analytics Harness picks the relevant context and routes each query. On top sit conversational BI, Live Apps generated from a prompt, analytics agents that can create tickets, call APIs or notify teams under guardrails, and Proactive Agents (launched September 2025) that monitor KPIs, run root-cause analysis on deviations and send alerts with charts and SQL. Analytics can be embedded through an iFrame, React SDK or GraphQL API, and a WisdomAI MCP server lets Claude, ChatGPT or other agents use the context engine. It runs as SaaS, in a customer VPC or on premises, with bring-your-own-LLM support. Named customers include ConocoPhillips, Cisco, Descope and Patreon, and the CEO reported about 40 enterprise customers in November 2025.
A head of data or BI at a large enterprise whose team is buried in ad-hoc dashboard and SQL requests from business users.
Business users get governed, query-backed answers in plain English, and the data team's request queue shrinks.
At a Glance
- Category
- Business Intelligence
- Pricing
- Subscription, Contact for pricing
- Target Market
- CIOs, CDOs, Heads of Data, BI Leaders, Business Analysts
- Deployment
- Cloud-first, Self-hosted, Hybrid
- Founded
- 2023
- Headquarters
- San Francisco, United States
- Customers
- About 40 enterprise customers (CEO, November 2025)
Key Features
- ✓Enterprise Context Layer
Learns each customer's schemas, metrics and business vocabulary and updates from feedback, which is what keeps answers consistent across users.
- ✓Query-only LLM design
The model writes the warehouse query and never the answer, so a hallucination yields a failed query instead of a wrong figure.
- ✓Conversational BI
Users ask plain-English questions across structured, semi-structured and unstructured sources and get charts backed by the generated query.
- ✓Proactive Agents
Monitor KPIs continuously, run root-cause analysis on deviations and send alerts with charts, SQL and a plain-language summary.
- ✓Analytics agents with actions
Agents query multiple sources and can create tickets, trigger APIs or notify teams under guardrails, turning insight into follow-through.
- ✓Embedded analytics and MCP
Embeds through iFrame, React SDK or GraphQL API with white-labelling, and exposes the context engine to Claude or ChatGPT over MCP.
- ✓Flexible deployment and governance
Runs single-tenant as SaaS, in a customer VPC or on premises, with bring-your-own LLM and query-time row and column security.
Capabilities
Use Cases
- •Self-serve analytics for business users
Sales and marketing staff ask questions in plain English and get governed answers without filing a request with the data team.
- •KPI anomaly detection
A Proactive Agent spots a metric deviation, identifies the affected segment and time frame, and alerts the owner with evidence.
- •Embedded customer-facing analytics
A software vendor embeds WisdomAI's agentic analytics in its own product through the React SDK under its own branding.
- •Agent access to governed data
An internal Claude or ChatGPT deployment queries enterprise metrics through WisdomAI MCP with row-level security still applied.
- •Seat expansion across the business
The CEO told TechCrunch that one customer grew from 10 to 450 seats as non-technical teams adopted self-serve querying.
Ideal For
Best For
- ✓Enterprises that want natural-language self-serve analytics for non-technical staff over existing warehouses
- ✓Data teams that need row- and column-level security enforced at query time on AI answers
- ✓Regulated companies that must run analytics in their own VPC or on premises with their own LLM
- ✓Product teams embedding agentic analytics into their own application with white-labelling
- ✓Operations teams that want KPI monitoring with automatic root-cause analysis and alerts
Not Ideal For
- ✗Small teams or budget-constrained buyers, since there are no public prices and year-one cost includes context onboarding and connectors
- ✗Buyers who want many independent peer reviews before a shortlist; G2 and Capterra coverage is sparse and most review volume is about 15 Gartner Peer Insights reviews
- ✗Organisations without staff to maintain the business context layer, which RFP.wiki describes as a heavier buyer responsibility
Integrations
Deployment
Market & Ratings
About 40 enterprise customers (CEO, November 2025)
Market Analysis
Pros
- ✓Gartner Peer Insights reviewers (4.6 across 15 reviews) praise natural-language querying and customer support
- ✓Query-only use of the LLM plus query-time row-level security addresses the main accuracy and governance worries about AI BI
- ✓VPC and on-premises deployment with bring-your-own LLM suits regulated industries
- ✓Production customers include ConocoPhillips, Cisco, Descope and Patreon
Cons
- ✗Pricing is opaque; RFP.wiki scores pricing 2.8 and cost controls for agentic workloads 3.2
- ✗Independent review volume is thin, with sparse G2 and Capterra coverage and one critical 3.0 Gartner review among few
- ✗Accuracy depends on how mature the context layer is, and keeping it maintained falls largely on the buyer
- ✗Accuracy and speed claims on the homepage (95%+ accuracy, 3x faster) are vendor figures with no published method
Pricing
Enterprise
Contact for pricing
- ✓Conversational BI and Live Apps
- ✓Analytics and Proactive Agents
- ✓Enterprise Context Layer
- ✓SaaS, VPC or on-premises deployment
- ✓Embedded analytics and MCP
WisdomAI publishes no prices or tiers; its pricing URL returned a 404 when checked on November 15, 2026, and the site routes buyers to sales. RFP.wiki describes it as custom enterprise subscription software and scores pricing transparency 2.8, warning that year-one cost can grow with context onboarding, connectors, security reviews and premium support. Its pricing evidence is labelled an estimate, and cost attribution for agentic workloads is not documented publicly.
Security & Compliance
Sources
This page was written from 7 sources, 5 on domains other than wisdom.ai.
- 1.wisdom.ai — wisdom.aivendor
- 2.wisdom.ai — aboutvendor
- 3.techcrunch.com — ai data startup wisdomai has raised another 50m led by klein
- 4.kleinerperkins.com — wisdomai series a
- 5.siliconangle.com — wisdom ai debuts agentic data analysts deliver continuous st
- 6.vcaonline.com — wisdomai raises 50 million to lead the next generation of ai
- 7.rfp.wiki — wisdomai
Stay Ahead of the Curve
Weekly enterprise AI insights for technology leaders. No spam, no vendor pitches—unsubscribe anytime.
SubscribeRelated Products
Qualitate
AI-native expert network: an AI interviewer and research agents that run primary research continuously
ThoughtSpot
Agentic analytics and BI platform where Spotter agents answer data questions, build semantic models and dashboards
OpenAI Data Agent
Natural-language data analysis and dashboards over your warehouse, inside ChatGPT Work