Fig AI

Fig is an AI platform designed to help individuals, teams, and enterprises research, create, analyze, and execute work using AI. The platform brings multiple AI models, company context, connected applications, AI agents, and governance controls into a single environment.

The current Fig platform is positioned as an enterprise AI platform rather than simply a chatbot. It combines frontier and open-source AI models with an agentic layer that can select an appropriate model for a task, access company information, use connected applications, and produce finished work. Fig describes this architecture as seven layers covering large language models, an agentic harness, data and integrations, context and knowledge, capabilities, products and surfaces, and security and governance.

At the center of the platform is Fig Assistant, an AI coworker that can understand company context, plan tasks, execute work, and produce finished deliverables. Fig also provides Fig Agents, which are designed for recurring and multi-step workflows. Organizations can create agents for specific roles and coordinate multiple agents to handle more complex processes.

Fig’s research and analysis capabilities allow users to ask questions and receive structured outputs such as plans, queries, charts, and cited findings. This makes the platform useful for research, business analysis, reporting, and decision support rather than limiting AI interaction to conversational responses.

The platform supports a broad range of content and work formats. Fig can assist with documents, presentations, spreadsheets, websites, mock-ups, images, video, audio, and other artifacts. Its business offering also includes scheduled tasks and deep research, allowing users to delegate more substantial pieces of work rather than simply asking for individual answers.

One of Fig’s notable capabilities is Fig Intelligence, which automatically routes tasks to appropriate AI models according to factors such as quality, modality, complexity, speed, and cost. The platform brings multiple model providers together through a model hub and provides usage controls for organizations that need to manage AI consumption.

Fig also provides an AI Gateway for organizations that want centralized management of AI models, tools, company context, and MCP servers. Administrators can monitor AI usage, manage model access, establish spending limits, and apply governance policies across AI applications.

Company context is another major part of the platform. Fig can connect business data and applications into a permission-aware enterprise context layer. This allows AI assistants and agents to use information from the systems employees already work with while maintaining the permissions of those source systems.

Fig supports more than 1,000 tools and data sources, according to its current website. Its connector ecosystem covers communication, productivity, CRM, finance, analytics, databases, development, and other business systems. Examples include Gmail, Slack, Google Drive, Google Calendar, Google Sheets, Notion, GitHub, Jira, Linear, Asana, HubSpot, Stripe, Shopify, Airtable, Snowflake, PostgreSQL, MySQL, MongoDB, Datadog, Docker, Cloudflare, Vercel, WhatsApp, and Telegram.

The platform can also operate directly within communication tools. Fig is available in Slack and supports WhatsApp and Telegram, while Microsoft Teams integration is listed as coming soon. Within connected applications, users can ask Fig to research, draft, analyze, and take actions. Consequential actions such as sending, creating, or deleting can be placed behind approval gates.

Developers can extend Fig through its open platform. The platform provides APIs, a web SDK, and headless MCP support. Fig specifically identifies Search API, Chat API, and Agents API capabilities, giving organizations options for embedding AI into their own applications and workflows.

For businesses, Fig can automate repetitive work and produce finished deliverables. Examples include preparing reports and slide decks, creating websites, running scheduled tasks, analyzing spreadsheets, and conducting deep research. The platform is designed so users can describe an outcome and allow Fig to carry out the necessary steps.

Fig also supports creative and multimedia workflows. Users can generate images, videos, and audio from prompts, while its artifact capabilities cover presentations, reports, spreadsheets, and mock-ups. Voice functionality allows users to interact with Fig in real time through spoken conversation.

Security and governance are central to Fig’s enterprise positioning. The platform provides granular permissions, role-based controls, audit trails, usage controls, approval mechanisms, and permission-aware access to connected data. Its enterprise platform is designed to allow organizations to adopt AI while maintaining control over company information and AI usage.

Fig is used across a wide range of departments and industries. Its website specifically highlights engineering, customer service, sales, IT, marketing, people, finance, and legal teams, as well as industries such as retail, manufacturing, supply chain, construction, education, financial services, insurance, government, and healthcare.

The platform is available across web, desktop, and mobile experiences, with a CLI also available. Fig’s current website reports more than 300,000 professionals using the platform across 70+ countries and more than 1,000 tools and data sources connected to it.

Fig is particularly suitable for organizations that want to consolidate multiple AI models and business workflows into one governed environment. Its combination of AI assistants, autonomous agents, research, content generation, automation, integrations, company context, and administrative controls makes it more comparable to an enterprise AI operating layer than a conventional standalone chatbot.

Pricing

Fig’s current website distinguishes between self-serve use for individuals and small teams and enterprise deployments. The platform promotes Try Fig free for users who want to get started, while enterprise customers are directed toward Get a demo / Contact sales for an organization-wide deployment.

Fig’s current pricing model is primarily usage-based rather than seat-based for team usage. Its integration page states that integrations are included and that usage is billed from a team’s shared credit pool rather than charging separately per seat or per connector.

Enterprise customers can use usage controls to establish organizational, departmental, individual, or agent-level limits. Administrators can monitor consumption, set alerts, forecast spending, and control model access.

Because Fig’s enterprise offering is customized around organizational requirements, the enterprise price is not publicly listed as a single fixed amount on the current official site.

Review

Fig is a broad AI platform aimed at organizations that want more than conversational AI. Its strongest feature is the combination of multiple AI models, agents, enterprise context, integrations, and governance in one platform.

The ability to connect Fig to business applications is particularly useful. Instead of requiring employees to copy information between different systems, Fig can retrieve information from connected sources and perform approved actions within those systems. Its large connector ecosystem also makes it adaptable to existing business workflows.

The automatic model-routing approach is another advantage. Instead of forcing users to decide which AI model is best for every task, Fig Intelligence can select models according to the requirements of the work. This can help organizations balance quality, speed, and AI spending.

Fig is also stronger than a basic AI assistant for automation. Its agent builder, agent orchestration, scheduled tasks, and work-execution features allow organizations to delegate recurring or multi-step processes.

The main limitation is complexity. Fig covers many functions, from AI chat and research to agents, integrations, model management, enterprise context, and governance. Organizations may therefore need time to configure the platform effectively and establish appropriate permissions and usage policies.

Another consideration is pricing. Fig’s usage-based model can be attractive because teams are not charged separately for every connector or necessarily by seat, but organizations with heavy AI usage need to monitor consumption and establish appropriate limits.

For businesses looking for a centralized AI platform that can connect to existing systems and execute real work, Fig is a strong option. It is especially compelling for teams that need enterprise context, AI agents, automation, multiple models, and centralized governance rather than a simple standalone chatbot.