Definite AI

Definite AI is the AI-native intelligence layer within Definite, an all-in-one data platform that combines data integration, a lakehouse, data transformations, a semantic layer, dashboards, data applications, automation, and AI-powered analytics. Its built-in AI analyst, Fi, allows business users and data teams to interact with company data using natural language instead of requiring every question to be answered manually with SQL.

The platform is designed to replace the collection of separate tools traditionally used for business analytics. Definite combines data ingestion, storage, transformation, modeling, business intelligence, and AI analysis in one environment. This allows users to connect business systems, centralize their data, define consistent metrics, create dashboards, and ask questions about the resulting data from the same platform.

Fi is the central AI experience. Users can ask questions about their business data in plain English, and Fi can interpret the request, query the underlying lakehouse, and return answers and visualizations. Definite’s website describes Fi as an AI analyst capable of writing queries and building charts. The platform’s semantic layer provides business definitions, measures, relationships, and other context that help the AI interpret data consistently.

The semantic layer is an important part of Definite’s AI architecture. It acts as a structured description of what the organization’s data means, including business names, dimensions, measures, relationships, synonyms, and metric definitions. This allows AI-generated analysis to use governed business context instead of relying only on raw database schemas.

Definite also supports AI agents. Its autonomous-agent system can monitor data, run SQL or Python probes, send the results to an LLM for evaluation, and take an action when specified conditions are met. Actions can include posting to Slack, triggering a webhook, running SQL, or handing work to a Fi agent. This allows Definite to move beyond passive analytics toward automated, event-driven data workflows.

The platform includes a Model Context Protocol (MCP) server, allowing external AI agents to interact with Definite. Definite states that agents such as Claude, Cursor, ChatGPT, and custom agents can access schema, lineage, and semantic context through MCP. This makes Definite useful as a governed data layer for external AI systems rather than only as a standalone analytics interface.

Data integration is another major part of the platform. Definite currently advertises more than 500 connectors covering SaaS applications, databases, files, APIs, and other data sources. Popular integrations include Stripe, HubSpot, Salesforce, PostgreSQL, Shopify, Google Analytics, MongoDB, Snowflake, Mixpanel, Intercom, Segment, NetSuite, and Airtable. It also supports CSV, Parquet, JSON, and NDJSON files and can connect to custom APIs.

Database replication is supported for sources such as PostgreSQL, MySQL, and Oracle through log-based change data capture where supported. Definite can also use SSH tunnels for databases located behind a bastion. This allows organizations to continuously synchronize operational data into the platform for analysis.

Definite combines analytics with automation. Users can schedule SQL transformations and Python scripts, send email reports, post Slack alerts, export data, synchronize information with Google Sheets, and perform automated writes. Python support also allows users to perform machine learning, natural-language processing, API calls, and data enrichment directly within the platform.

The platform provides an API for programmatic access. Its API can execute SQL queries, browse the data catalog, manage saved queries, interact with semantic models, work with transformations, and access other platform capabilities. Definite also provides a Python SDK for custom data workflows and integrations.

Definite supports data applications in addition to traditional dashboards. Its current platform positioning emphasizes custom data-heavy applications, interactive visualizations, tables, filters, and other interfaces that allow teams to turn data into operational tools rather than simply viewing static reports.

Security and deployment are also significant aspects of Definite. The platform can run as a private deployment in an organization’s own AWS, Google Cloud, Azure, or Kubernetes environment. Its documentation describes single-tenant deployments and multiple layers of access control, including application roles, resource sharing, and table-level data-access permissions. Enterprise plans add SSO, audit logs, SCIM, dedicated support, SLAs, and other governance capabilities.

Definite’s origins go back to 2023. The company published its initial public announcement in February 2023, describing Definite as a new analytics platform designed to automate tedious analytics work with AI and allow teams to create analytics workflows using natural language. LinkedIn currently lists the company as founded in 2023.

The platform has since evolved substantially from its original analytics-focused positioning. Current Definite combines an AI analyst with data ingestion, a lakehouse, semantic modeling, automation, dashboards, data applications, autonomous agents, MCP, and programmatic APIs.

Definite is particularly suited to startups, growing companies, analytics teams, operations teams, finance teams, marketing teams, and organizations that want to avoid assembling a large collection of separate data infrastructure and BI products. Its combination of AI analysis and underlying data infrastructure means that users can ask questions against connected business data while maintaining a consistent semantic model.

The platform is therefore best understood as a full-stack AI data platform rather than simply an AI analytics assistant. Its distinctive value comes from putting the AI analyst directly on top of the data pipelines, lakehouse, semantic layer, dashboards, automation system, and agent infrastructure.

Pricing

Definite currently offers three plans: Free, Standard, and Enterprise. The Free plan costs $0 forever and includes 2 users, 2 connectors, Fi AI Assistant, daily synchronization, 1 GB of storage, and 5 credits per month.

The Standard plan costs $250 per month and includes unlimited users, more than 500 connectors, API access, hourly synchronization, 10 GB of storage, and 100 credits per month.

The Enterprise plan uses custom pricing and adds capabilities such as SSO through SAML/OIDC, audit logs, SCIM, near-real-time synchronization, dedicated support, SLAs, and private deployment options.

Definite uses credits for compute and AI usage. One credit represents one compute-hour unit or 100,000 AI tokens. Additional credits on Standard cost $1 each.

Review

Definite AI stands out because its AI analyst is integrated into a complete data platform rather than operating on top of an external spreadsheet or BI environment. Fi can work with connected business data, the semantic layer, dashboards, and data applications, giving it access to more context than a general-purpose chatbot working from a manually uploaded file.

The semantic layer is particularly valuable. By defining business metrics, dimensions, relationships, and terminology centrally, organizations can give both users and AI agents a consistent understanding of company data. This can help reduce the ambiguity that often occurs when AI systems query raw tables without business context.

Another strength is the breadth of the platform. Definite combines more than 500 connectors, a lakehouse, transformations, dashboards, automation, AI analysis, autonomous agents, MCP, APIs, and Python support. This reduces the need for organizations to stitch together multiple separate tools for data ingestion, storage, analytics, and AI.

The autonomous-agent capabilities are also notable. Agents can monitor SQL or Python-based data probes, have an LLM evaluate whether an action is required, and then trigger actions such as Slack messages, webhooks, SQL operations, or Fi workflows. This gives Definite a stronger automation component than a conventional dashboarding product.

The main consideration is that Definite is a broad data platform, so it can be more involved than a lightweight AI spreadsheet or standalone data-analysis assistant. Organizations need to connect their sources, establish appropriate models and permissions, and determine how their semantic layer should represent business metrics.

Pricing is also higher for teams that move beyond the free tier. The Standard plan begins at $250 per month, although it provides unlimited users and a large connector catalog. Enterprise organizations may need custom pricing for advanced security, deployment, and support.

Definite is therefore a strong option for teams that want AI-powered analytics, governed business data, data integration, automation, and AI agents in one platform. It is particularly compelling for organizations that would otherwise need several separate products to build and maintain their data stack.