Definite

What Definite does

Definite is an AI-native data platform that centralizes all data for analytics and dashboards, requiring no engineering or SQL. It provides a managed data warehouse, ELT, data modeling and transformations, and AI-assisted business intelligence in a single platform. The platform allows users to ask questions in plain English, ship full data applications, and integrate with over 500 data sources. It aims to replace fragmented data stacks with a unified, AI-powered solution, offering features like AI agents, custom data apps, and a governed semantic layer.

Products

• Definite PlatformA comprehensive AI-native data platform offering connectors, storage, modeling, BI, and an AI analyst. It replaces multiple data stack vendors with a single, integrated solution for data centralization, analytics, and AI-driven insights.
• Fi (AI Analyst)Definite's built-in AI analyst that answers questions in plain English, writes SQL, builds data apps, ships dashboards, and explains numbers. It operates on a governed semantic layer to ensure consistent metrics.
• Data Team as a Service (DTaaS)An add-on service providing senior data engineers to set up data stacks, build dashboards, and run analytics. It offers unlimited requests for connector setup, dashboard building, and data modeling, acting as an outsourced data team.
• Definite On-Prem/BYOCA private deployment option for the Definite platform that runs in the customer's own cloud environment (AWS, GCP, Azure, or any Kubernetes cluster). It ensures data residency and compliance for regulated industries by keeping all data and processing within the customer's infrastructure.

Key capabilities

• 500+ native connectors for data integration
• Managed data warehouse (Iceberg lakehouse powered by DuckLake)
• ELT (Extract, Load, Transform)
• Data modeling and transformations
• AI-assisted business intelligence
• AI agents (Fi, Claude, Cursor, MCP)
• Plain English querying for analytics
• Data apps (custom visualizations, bespoke data-heavy applications)
• Sub-second search across millions of rows in the browser
• Semantic layer for consistent metric definitions
• Versioned YAML for metrics (metrics as code)
• Role-based access control (RBAC)
• Full audit trail
• Encryption in transit and at rest
• SSO (SAML/OIDC)
• SCIM provisioning
• Row-level security
• Vulnerability management
• Daily encrypted backups
• Data residency options (US, EU)
• Automated writes and external syncs (data activation)
• Email and Slack alerts
• Exports (CSV, Excel, JSON)
• API access
• Python Runner for custom analysis
• Metrics API
• Embeddable Charts
• Custom data sources
• Near real-time sync
• On-premise deployment available

Use cases

• Centralizing data for analytics and dashboards
• Building custom data applications
• Asking data questions in plain English
• Understanding product usage, customer context, and business outcomes
• Fast feedback on product changes and their impact on retention, expansion, and revenue
• Connecting product usage to accounts, segments, and revenue
• Identifying changes in user behavior after releases
• Prioritizing product improvements
• Analyzing user engagement with core features
• Connecting support tickets and feedback with usage
• Spotting user drop-off points
• Consolidating data stacks (replacing multiple BI tools, databases, reporting pipelines)
• AI analytics initiatives
• Fintech and lending analytics (loan management, CRM, payment processor integration)
• Unified reporting across multiple Google Ads MCC accounts
• Marketing and growth performance analysis
• SaaS data platform for metrics like MRR, churn, NRR, activation
• Startup data platform for quick setup of core business metrics
• Founders & CEOs getting clear, reliable answers across the business
• Finance leaders unifying billing, accounting, and revenue data
• RevOps & Sales Ops leaders unifying CRM, billing, and pipeline data for consistent metrics and forecasting
• Marketing leaders bringing together performance data for faster decisions
• Product leaders understanding user behavior and product success
• Customer Success leaders spotting churn risk and prioritizing outreach
• Automating reports and analyses
• Connecting any agent (Claude, ChatGPT, Gemini) to data via MCP
• Deploying AI analytics in regulated industries with data residency requirements
• Achieving board-ready analytics quickly
• Reducing analyst bottlenecks by enabling self-service data access

AI approach

Definite provides an AI-native data platform with a built-in AI analyst named Fi, and supports integration with other AI agents like Claude, Cursor, ChatGPT, and Gemini. Fi can answer questions in plain English, write SQL, build data apps, and automate tasks. The platform uses a governed semantic layer to ensure AI agents query defined metrics, maintaining consistency and trustworthiness of data. Definite also offers autonomous agents that can watch data and act on their own. The AI capabilities are deeply integrated into the platform, allowing for AI-assisted business intelligence, data modeling, and transformations.

Tech named: Fi (AI analyst), Claude, Cursor, MCP (Model Context Protocol), ChatGPT, Gemini, DuckDB-Wasm, DuckLake, Iceberg, Kubernetes, Helm chart, Rust CLI, PostgreSQL, S3, GCS, AWS Bedrock, Google Vertex AI, Azure OpenAI

Industries served

• Data Infrastructure and Analytics
• Fintech
• Lending
• Wealth-Tech
• Financial Advice Firms
• SaaS
• Talent Acquisition
• HR Tech
• Specialty Lending (Solar + Home Improvement)
• Finance
• Cyber
• Regulated Industries

What it says sets it apart

• AI-native platform from the ground up, not AI bolted on top of existing solutions
• Consolidates entire data stack (connectors, storage, modeling, BI, AI analyst) into one platform
• No engineering or SQL required for setup and use
• AI agents (Fi) can build full data applications, not just charts
• Governed semantic layer ensures consistent metrics across all tools and agents
• Unlimited users with one flat price, no per-seat pricing
• Starts free and scales with credit-based compute and AI usage
• Open formats (Iceberg lakehouse, Parquet) and zero lock-in
• Browser-native speed with sub-second search across millions of rows (DuckDB-Wasm)
• Ability to bring your own AI agents (Claude, ChatGPT, Gemini) and connect them to governed data via MCP
• On-premise/BYOC deployment for data residency and compliance in regulated industries
• Rapid implementation (e.g., board-ready analytics in 7 days, full data infrastructure in two weeks)
• Data Team as a Service (DTaaS) offering senior data engineers without hiring overhead
• Replaces multiple siloed systems with a single source of truth
• Focus on clear answers and actionable insights for business leaders

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.