AI ToolAI Agents

Flue

Flue is an open-source TypeScript framework for building durable AI agents with persistent state, multi-channel connectivity, and flexible deployment.

Flue is an AI agent, integrating with Slack, Teams, Discord, and GitHub. InnovaAI scores it 4.6/10 for agency adoption, best for Backend Engineer, Technical Lead, and Operations Manager roles handling 5+ client meetings per week.

Situational Fit4.6/10

Agency Audit

Flue is an open-source TypeScript framework for building and deploying stateful AI agents with persistent memory, multi-channel connectivity, and LLM flexibility. Agencies building custom automation solutions, internal workflow orchestration, or client-facing agent products benefit most from adopting Flue internally. The framework's React-like hooks API, deployment flexibility across Node.js, Cloudflare, and GitHub Actions, and native integrations with Slack, Discord, Teams, and business tools like Stripe and Notion make it a strong fit for technical teams automating repetitive internal processes or prototyping agent-based client deliverables.

Situational FitNo WLOpen Source
Seats

3recommended

Est. Hours Saved

36/mo

Net Capacity

No paid plan published

Friction

Moderate

Illustrative scenario. Not a guarantee. Net capacity needs a verified paid base plan, and none is published for this service, so it is not modeled. Hours saved come from the service estimate; implementation, taxes, and unprovided usage charges are excluded.

Situational Fit
Fit46
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Best For Your Team
  • Backend Engineer handling multi-channel integration development
  • Technical Lead handling long-running workflow automation
  • Operations Manager handling state management for interrupted tasks
Not Ideal If
  • Your team lacks TypeScript expertise and cannot allocate an engineer to learn the framework. Flue is not a visual builder; it requires code-first development.
  • You need agents deployed and running within days, not weeks. Flue's learning curve and the need to define custom tools and skills mean initial agent development takes 2-4 weeks for a non-trivial workflow.
  • Your workflows are simple enough for existing no-code automation tools like Zapier or Make. Flue's complexity overhead is only justified for multi-step, stateful, or highly customized agent behavior.

Internal Adoption Path

Team Subscription

No paid plan published

Time Saved Monthly

36 hr/mo

3 seats × 12 hr each

Value of Reclaimed Time

$2,700/mo

modeled at $75/hr labor rate

Net Capacity

No paid plan published

Illustrative scenario. Not a guarantee. No verified paid base plan is published for this service, so subscription cost and net capacity are not modeled. Implementation, taxes, and unprovided usage charges are excluded.

Platform Features

Core capabilities of Flue

React-like hooks API for agent behavior

Developers define agent logic using familiar hooks patterns, reducing the learning curve for teams already comfortable with React. This cuts the time for engineers to write their first production agent from weeks to days.

Persistent state and automatic resumption

Agents maintain context across sessions and resume interrupted work without manual intervention. Project managers and operations staff no longer need to manually restart failed workflows or re-enter context.

Multi-channel connectivity

Single agent codebase connects to Slack, Teams, Discord, GitHub, Twilio, WhatsApp, Telegram, and Google Chat. Technical operations teams eliminate the need to build separate integrations for each communication platform.

Flexible deployment across runtimes

Deploy agents to Node.js, Cloudflare Workers, GitHub Actions, AWS, Railway, Render, Fly, or Docker without code changes. Engineering teams avoid vendor lock-in and can migrate infrastructure without rewriting agent logic.

Tool and skill definition framework

Agents call APIs and perform actions through a declarative tool system. Developers spend less time writing boilerplate integration code and more time defining business logic.

Session trace export to observability platforms

Export traces to OpenTelemetry, Braintrust, or Sentry for debugging and monitoring. Technical leads gain visibility into agent decisions and can diagnose failures without digging through logs.

What Makes Flue Different

Unique advantages vs similar tools in this niche

Durable streams ensure agents never lose work and resume automatically after crashes

vs Stateless agent frameworks that lose context on failure

Flue records every session in a durable stream and safely resumes interrupted work when the runtime comes back online.

React-like hooks API for building agents in TypeScript

vs Traditional imperative agent coding

Use hooks like usePersistentState and useModel to manage state and model selection declaratively.

Deploy anywhere with support for Node.js, Cloudflare, and CI environments

vs Locked-in cloud-specific agent platforms

Write once and deploy to Node.js, Cloudflare, GitHub Actions, GitLab CI, and more.

Latest Updates

Recent releases and improvements for Flue

Flue 2.0, Introducing Agent Hooks

New

Release of Flue 2.0 introducing Agent Hooks feature.

Value Equation

Outcome-likelihood-time-effort assessment for Flue

Value math requires real pricing

The Value Equation (dream outcome × likelihood ÷ time × effort) feeds directly into ROI math. Flue has no published pricing, so we hold this section until real numbers are available.

Contact Flue

Pricing

Pricing data not yet available for Flue.

Reality Check

Trade-offs & Gotchas

Flue requires TypeScript proficiency and assumes your team can manage deployment infrastructure or cloud platforms. The learning curve is steeper than no-code agent builders, and ROI depends on having workflows complex enough to justify custom agent development rather than off-the-shelf automation tools.

Implementation Reality

High effort: requires technical configuration and team training

Effort: 4/10Time: 4/10

How This Accelerates White-Label Services

Who It's For

  • ai-development-agencies
  • automation-consultancies
  • software-agencies-building-custom-agent-solutions

Acceleration Steps

  1. 1Schedule onboarding with the vendor
  2. 2Configure build durable ai agents with a react-like hooks api in typescript
  3. 3Connect Slack
  4. 4Launch your first client project

Academy for Flue

Work through it in order: the course for this service first, then the modules behind it.

Core concepts

The mental model you need to price and scope the work.

  1. Wiring Over WidgetsConcept

    The AI agent itself is a commodity, but the value for agencies lies in the integration layer: connecting a pre-built agent to a client's CRM, calendar, and review cycle. This framework shifts focus from selecting the 'best' agent to mastering the wiring process. For example, an agency using Vendasta's white-label AI receptionist for a local business must configure it to match the client's booking rules and follow-up cadence, turning a generic tool into a tailored service. As agentic AI adoption grows (77% of decision-makers now run agents in production), clients expect this customization. Agencies that treat agents as components and invest in repeatable wiring processes can charge retainers for ongoing optimization, rather than one-off setup fees.

  2. Wiring Over WidgetsConcept

    The AI agent market sells finished workers, but the strategic value for agencies lies not in the agent itself, which is increasingly a commodity, but in the wiring that connects it to a specific client's CRM, calendar, and review cycle. This framework, 'Wiring Over Widgets,' argues that agencies that treat agents as components rather than products win. The agent is the widget; the wiring is the integration, customization, and ongoing optimization that turns a generic tool into a tailored solution. For example, a white-label platform like Vendasta provides AI employees, but the agency's role is to configure them for each local business's unique lead flow and follow-up process. This wiring is where retainer pricing originates, as it requires ongoing maintenance and adjustment. Recent research shows that 88% of B2B marketers face foundational gaps, meaning clients need help not just deploying agents, but ensuring their operations can support them. Agencies that master the wiring can charge a premium for the irreducible value they add.

  3. Integration MoatConcept

    The Integration Moat framework holds that the durability of an AI agent engagement is determined by how deeply the agent is wired into a client's existing systems, not by the agent's underlying capability. Since the agent itself is increasingly a commodity, the switching cost for the client lives in the integrations: the CRM fields mapped, the calendar sync, the review-cycle triggers, and the exception-handling rules. Agencies that invest in this wiring create a moat that competitors offering generic agents cannot cross. For example, a white-label platform like Vendasta lets an agency deploy an AI receptionist for a local business, but the real value is in configuring it to the client's booking flow and follow-up cadence. With 77% of AI decision-makers now running agentic AI in production, clients expect this depth, and agencies that deliver it convert one-off projects into retainers.

8 modules selected for Flue

Frequently Asked Questions

Answers about pricing, setup

Flue is an open-source TypeScript framework for building stateful AI agents that persist memory across sessions, connect to multiple communication channels like Slack and Discord, and deploy to any runtime including Node.js, Cloudflare, and GitHub Actions. Agents define tools and skills to call APIs and perform actions, and can be orchestrated as workflows. Session traces export to observability platforms like OpenTelemetry and Braintrust for production debugging.

Flue is open-source and free to use. There is no per-seat pricing, subscription fee, or commercial license required. Your only costs are infrastructure for deployment and any third-party LLM API calls your agents make.

Backend engineers and technical leads benefit most, as they write and maintain agent code. Operations and project management teams gain indirect value by automating repetitive workflows across Slack, Linear, Notion, and Stripe. Agencies building custom agent solutions for clients see the highest ROI, as Flue eliminates the need to build agent infrastructure from scratch for each project.

Time savings depend on your current workflow. Teams manually building multi-channel integrations or hand-coding state management for long-running tasks typically reclaim 4-8 hours per engineer per month once an agent is in production. Agencies building custom agents for clients compress agent development time by 30-40 percent compared to building integrations from scratch, translating to 6-12 hours saved per project.

Engineers familiar with TypeScript and React can write their first agent in 2-3 days. Teams new to agent development or TypeScript should budget 1-2 weeks for the first production agent. The hooks API and documentation reduce friction compared to building agents from first principles.

Yes. Flue is built on Pi, an agent harness that supports any LLM provider through its provider ecosystem. You can use OpenAI, Anthropic, Mistral, or any other LLM without changing agent code.