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Intentflow is a YAML-based UX flow engine that lets you define, trigger, and optimize user journeys in your frontend. It supports dynamic flags, conditional components (modals, tooltips, banners), optional LLM logic for adaptive rendering.

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Intentflow

Intentflow Hero

Intentflow is an open-source UX flow framework that lets product teams ship contextual onboarding, nudges, and promotions in minutes—not days.

Read the full launch post on the Mixpeek blog: Intentflow – Open-Source UX Flow Engine

✨ Why Intentflow?

  • Declarative – author complex interaction flows in simple YAML.
  • Stateful – flags track user milestones across pages and sessions.
  • Pluggable – integrate analytics (PostHog), LLMs (ChatGPT, Claude, Gemini) or your own logic to decide which component to show.
  • Framework-agnostic – React-first, with Vue/Svelte adapters on the roadmap.

Use it to:

Outcome Example Context Component
Increase trial → paid conversions User viewed pricing but didn't upgrade Modal
Collect qualified leads User hit a feature paywall Banner
Guide power users to hidden gems User hovers a rarely-used feature toggle Tooltip
Drive webinar sign-ups Docs readers spending >3 min on tutorials Modal

🏃‍♂️ Quick Start

# 1. Install peer deps
npm install react
# 2. Install Intentflow package
npm install intentflow
import {
  IntentflowProvider,
  useUXFlag,
  useUXStep,
  useUXGoal,
  Modal,
} from 'intentflow';

function App() {
  return (
    <IntentflowProvider>
      <YourRoutes />
    </IntentflowProvider>
  );
}

Example YAML Flow

# public-flows/example.yaml

goals:
  schedule_meeting:
    steps:
      - id: viewed_pricing
        event: page_view
        path: "/pricing"
        set_flag: viewed_pricing
      - id: clicked_cta
        event: click
        selector: ".cta-button"
        requires_flags: [viewed_pricing]
        set_flag: interested_user

Load and evaluate this flow:

import { loadFlowFile } from 'intentflow';

const flow = loadFlowFile('public-flows/example.yaml');

📈 Analytics Integrations

Provider Focus OSS? Init Example
PostHog Product analytics with feature flags Yes initPostHog('PH_KEY', { api_host: 'https://app.posthog.com' })
Amplitude Product analytics, growth insights No initAmplitude('AMP_KEY')
Heap Auto-captured event analytics No initHeap('HEAP_APP_ID')
RudderStack Customer data pipeline / CDP Partial initRudderStack('WRITE_KEY', 'https://rs.example.com')
Snowplow Behavioral data platform Yes initSnowplow('https://collector.acme.com')
Matomo GDPR-focused web analytics Yes initMatomo('SITE_ID', 'https://matomo.acme.com')

Every time a flag is set, Intentflow automatically fires intentflow_flag_set to PostHog. You can subscribe to additional events via your own code or use PostHog dashboards to correlate UX experiments with conversions.


🤖 LLM-Driven Decisioning

Intentflow ships with a lightweight Evaluator that can call ChatGPT (OpenAI), Gemini (Google), or Claude (Anthropic) to decide which components to render.

import { Evaluator } from 'intentflow';

const evaluator = new Evaluator('openai', process.env.OPENAI_API_KEY!);

const decision = await evaluator.evaluate({
  flags: { viewed_pricing: true },
  components: [{ id: 'modal1', type: 'modal' }],
  goal: 'schedule_meeting',
  page: '/pricing',
});

// decision.render -> ['modal1']
// decision.set_flags -> ['modal_shown']

Swap providers with a single arg:

new Evaluator('gemini', GCP_API_KEY);
new Evaluator('claude', ANTHROPIC_KEY);
Provider Model Family Init Example
OpenAI ChatGPT GPT-3.5 / GPT-4 new Evaluator('openai', OPENAI_KEY)
Google Gemini Gemini-Pro new Evaluator('gemini', GEMINI_KEY)
Anthropic Claude Claude 3 new Evaluator('claude', ANTHROPIC_KEY)

🔌 Integrating with Mixpeek

Intentflow pairs seamlessly with Mixpeek to bring intelligent UX flow optimization powered by multimodal retrieval, classification, and clustering.

✅ What Mixpeek Adds

  • Semantic Flow Matching → Retrieve the most relevant YAML-defined flow based on user session summaries, not just static rules. "User hovered CTA, watched demo, abandoned signup" → → flow: schedule_meeting.

  • Component Effectiveness Clustering → Mixpeek clusters historical sessions (flags, outcomes, component usage) to surface which combinations of tooltips, banners, or modals worked best for each intent.

  • Multimodal Context Classification → Classify sessions not just from flags or clicks, but video/audio inputs, transcript data, screenshots, etc. E.g., "User watched a feature walkthrough video but skipped the pricing page."

  • Searchable UX Memory → Store all sessions as structured documents and search them:

    await mixpeek.search("Sessions where modals failed but tooltips worked");
  • Cookieless Personalization → Use vector embeddings and session semantics to adapt the UI—no ID tracking required.

🧠 Example

import { retrieveFlow, rerankComponents, logSession } from 'intentflow/mixpeek';

const flow = await retrieveFlow("User clicked pricing, hovered CTA, did not convert");

const ranked = await rerankComponents({
  flags: { viewed_pricing: true, clicked_cta: false },
  goal: "schedule_meeting",
});

await logSession({
  flags: ["viewed_pricing", "tooltip_shown"],
  outcome: "no_conversion",
  goal: "schedule_meeting"
});

Mixpeek transforms your UX flows into a searchable, improvable, intent-driven system—powered by real multimodal session intelligence.


🗺 Roadmap / Contributing

  • Live session inspector / devtools overlay – debug flows and flags in-browser
  • LLM prompt builder playground – test & refine evaluator logic in-browser
  • Vue/Svelte adapters – expand beyond React
  • Analytics adapters (RudderStack, Amplitude) – drop-in integrations
  • Mixpeek-powered flow search & clustering UI – see which flows are performing best
  • Component variant testing – show alternate tooltips/modals for same step

PRs & issues welcome! 🎉

About

Intentflow is a YAML-based UX flow engine that lets you define, trigger, and optimize user journeys in your frontend. It supports dynamic flags, conditional components (modals, tooltips, banners), optional LLM logic for adaptive rendering.

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