Superflows - Add AI assistants to your product without an AI team

What Is Superflows

Building an AI assistant for your SaaS product sounds like a project for a dedicated AI team—but what if your product team could ship one in weeks instead of months? That's exactly what Superflows enables. It's a developer-first platform that lets you embed a powerful AI copilot directly into your product without needing machine learning expertise or an AI engineering team.

The core idea is elegantly simple: you upload your OpenAPI specification, and Superflows automatically builds an AI assistant that can call your product's APIs to fetch real-time data, execute actions on behalf of users, and answer static knowledge questions using RAG (retrieval-augmented generation). Your users get a natural language interface to your product, while your team avoids the complexity of building AI infrastructure from scratch.

Superflows was built specifically for SaaS companies by a London-based team with backgrounds from Oxford, Cambridge, and UCL. They've already helped companies like Ontik and Integrated Finance ship AI assistants that their customers love. The platform is also fully open-source—you can find the code on GitHub and even self-host it if you prefer.

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Core Features That Power Your AI Assistant

What can Superflows actually do for your product? Let's break down the capabilities that make it tick.

Analytics: Get Answers in Seconds, Not Hours

Your users shouldn't need to navigate complex dashboards or wait for a support ticket to get insights. With Superflows, users simply ask questions like "Did our Google Ads campaign last month have positive ROI? How many conversions did it generate?" The AI calls your product APIs, processes the numbers, and delivers a clear answer—turning what used to take hours into a matter of seconds.

Actions: Let AI Work on Your Users' Behalf

Superflows goes beyond answering questions—it can actually do things. Users can say "Eve is sick today, please forward her calls to team members who have previously engaged with potential customers," and Superflows will prepare the action and request confirmation before executing it. This transforms passive AI assistants into active productivity tools.

Documentation Assistant: Instant Expert Help

Using RAG technology, Superflows can answer questions about your product's features, configuration options, and best practices. Users get instant answers to "how do I configure X?" questions without your support team having to repeat themselves.

Developer Tools: Built for Engineering Teams

The platform gives developers a full toolkit: upload your OpenAPI spec to auto-build the assistant, test everything in the Playground with mock API responses (no need to connect to production APIs during development), and integrate the React UI component with just one line of code. The developer dashboard lets you configure and debug every aspect of the assistant's behavior.

Multi-LLM Flexibility

Choose the right model for your needs and budget. Superflows supports Fine-tuned GPT-3.5, GPT-4, Mixtral, Llama2, and other models. You can run on cloud-hosted models for simplicity or self-host for complete data control.

Continuous Improvement

Superflows collects user feedback on AI responses, which you can use to fine-tune and improve the assistant over time.

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Who Is Using Superflows

Superflows serves a range of SaaS teams, from startups to established companies. Here's how different teams are putting it to work.

CRM Copilot: Activating More Users

CRM platforms are powerful but notoriously difficult to learn. Users often give up before discovering the value. By adding an AI copilot that lets users accomplish tasks through conversation—"Show me deals closing this month" or "Create a follow-up task for this lead"—companies using Superflows are activating more users, improving retention, and closing more deals. The AI guides users through complex workflows without requiring them to master the interface.

Reducing Dashboard Development Cycles

Engineering teams constantly build new dashboards to meet user requests for specific charts and reports. With Superflows, users can simply ask for any visualization they need: "Show me revenue by region for Q3" or "Compare our churn rate against last year." This dramatically reduces the dashboard backlog—one Superflows customer estimated saving 6 months of development time, shrinking requests from a 6-month roadmap to a few weeks of configuration.

Boosting User Engagement and Retention

When users struggle to find value in your product, they churn. Superflows helps by providing proactive guidance and insights—surfacing features users haven't discovered, explaining complex configurations, and helping users achieve their goals faster. The AI acts like a knowledgeable teammate who's always available.

Empowering Non-Technical Teams

Traditionally, only engineers could solve complex customer issues that required querying databases or manipulating data. Superflows changes this: customer success teams, sales operations, and support staff can now handle sophisticated queries that previously required developer intervention. As Alistair Cotton, CEO of Integrated Finance, put it: "Superflows enables our non-technical team to solve complex customer problems that only engineers could previously handle."

What Customers Say

Ontik's CEO Chris Smith shared: "We just launched our Superflows-powered feature and early users love it. Excellent team, excellent product." These aren't just logos—they're teams shipping AI features their customers actually use.

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Getting Started Quickly

Ready to add an AI assistant to your product? Here's how to go from sign-up to your first working demo.

Step 1: Sign Up for the Developer Dashboard

Head to dashboard.superflows.ai and create your account. You'll get access to the full configuration panel where you'll build and manage your AI assistant.

Step 2: Upload Your OpenAPI Specification

This is the magic step. Upload your OpenAPI (Swagger) spec, and Superflows automatically understands what your APIs can do. It uses this to build the AI's understanding of your product's capabilities—no manual endpoint mapping required.

Step 3: Test in the Playground

The Playground is your testing environment. You can interact with your AI assistant, try different queries, and see how it responds. Use Developer Mode to watch the AI's reasoning process—exactly what it's thinking when it answers. The Mock API Responses feature lets you test behavior without connecting to real APIs, which is invaluable for development.

Step 4: Integrate the UI

When you're ready to ship, adding the chat interface to your product takes one line of code using the React component. It handles the full conversation UI, streaming responses, and user feedback collection out of the box.

Step 5: Configure and Deploy

Set up your preferred LLM, configure safety settings (like requiring confirmation for destructive actions), and define any custom behaviors through the dashboard. The stateful streaming API ensures a smooth, responsive experience for your users.

Resources to Help You Along

• Documentation: docs.superflows.ai
• GitHub (open-source): github.com/Superflows-AI/superflows
• React components: github.com/Superflows-AI/chat-ui
• Public roadmap: docs.superflows.ai/blog/roadmap

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Technical Deep Dive

For engineering teams evaluating the technical fit, here's how Superflows works under the hood.

API-First Architecture

Superflows is designed around your existing APIs. When a user asks a question, the AI determines which API calls to make, executes them, processes the results, and delivers a natural language response. This means your AI assistant always has access to real-time, accurate data—nothing is hardcoded or outdated.

RAG for Static Knowledge

For questions that don't require live API data—like "How do I set up two-factor authentication?" or "What does the Pro plan include?"—Superflows uses retrieval-augmented generation. It searches your documentation, finds the relevant information, and generates accurate answers. This keeps your help docs accessible without manual maintenance.

Multi-LLM Support with Full Flexibility

The platform supports multiple LLM providers, including Fine-tuned GPT-3.5, GPT-4, Mixtral, and Llama2. You choose whether to run on cloud-hosted models (simplest setup) or self-host (complete data control). The architecture is provider-agnostic, so you can switch models as your needs evolve.

Safety and Control

Superflows includes multiple layers of safety: configurable answer format approval, mandatory user confirmation for dangerous actions (like deleting data or making payments), and a developer dashboard that gives you full control over what the assistant can and cannot do. You're never handing over the keys—the AI operates within boundaries you define.

Developer Experience

The Playground's Developer Mode reveals the AI's chain-of-thought, showing exactly which APIs it plans to call and why. Mock API Responses allow full testing cycles without touching production systems. The React UI component handles stateful streaming, so users see responses appear in real-time—matching the experience users expect from modern AI products.

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Frequently Asked Questions

<card type="faq" title="What exactly is a "Chat-to-API query"?"> A Chat-to-API query is any message from a user that triggers an API call to fetch data or perform an action. In the pricing, this is the primary metered resource. A simple question like "What's my current ARR?" that requires one API call counts as one query. Complex multi-step workflows might trigger several API calls per user message.