Value Platform

Outcome-based billing and payments infrastructure for AI agents. Meter usage, configure flexible pricing, and track profitability — so you can focus on building great AI products.

Overview

Value Platform handles metering, pricing, billing, and revenue tracking for AI agents:

• AI-Native Metering — Track tokens, LLM calls, API usage, and outcomes with minimal code
• Flexible Pricing — Fixed-Fee, Usage-based, tiered, per-action, per-outcome, or any combination
• Cost Attribution — Automatically allocate costs across LLM providers, APIs, and compute
• Revenue Insights — Real-time profitability tracking per agent and per customer

Start Tracking Your AI Agents

Choose your deployment option and start metering in minutes:

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☁️ Option 1: Use Value Cloud

The fastest way to get started — no infrastructure to manage.

Step 1: Sign up at 👉 value.valmi.io

Step 2: Install the SDK and start tracking:

pip install value-python

from value import initialize_sync

client = initialize_sync(agent_secret="your_agent_secret")

with client.action_context(user_id="user_123", anonymous_id="anon_456") as ctx:
    ctx.send(
        action_name="document_processing",
        **{"value.action.description": "Processing invoice", "document_type": "invoice"},
    )

That's it! Your agent data flows to Value Cloud automatically.

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🏠 Option 2: Self-Hosted Deployment

Run Value Platform on your own infrastructure for complete control.

Step 1: Start the services

# Prerequisites: Docker & Docker Compose, Make

# Configure environment
cp value-engine/.env.example value-engine/.env
cp value-control-plane-backend/.env.example value-control-plane-backend/.env

# Start all services
make value-up

Step 2: Install the SDK and point to your local instance:

pip install value-python

# Set environment variables
export VALUE_BACKEND_URL=http://localhost:8200
export VALUE_OTEL_ENDPOINT=http://localhost:4317

from value import initialize_sync

client = initialize_sync(agent_secret="your_agent_secret")

with client.action_context(user_id="user_123", anonymous_id="anon_456") as ctx:
    ctx.send(action_name="document_processing", **{"document_type": "invoice"})

Step 3: Access your dashboard

Service	URL
Value UI	http://localhost:3000
Control Plane API	http://localhost:8200/docs
Engine API	http://localhost:8000/docs
Celery Flower	http://localhost:5555

# Stop services
make value-down

# Clean all data volumes
make value-clean-volumes

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📖 See sdks/ for detailed SDK documentation.

Architecture

┌─────────────────┐                              ┌─────────────────┐
│   Value SDK     │─────────────────────────────▶│  Value Engine   │
│  (Python/Node)  │                              │  (Processing)   │
└─────────────────┘                              └────────┬────────┘
                                                          │
                                                          ▼
┌─────────────────┐     ┌──────────────────┐     ┌─────────────────┐
│    Value UI     │◀───▶│  Control Plane   │◀───▶│   Data Store    │
│   (Dashboard)   │     │      (API)       │     │                 │
└─────────────────┘     └──────────────────┘     └─────────────────┘

Screenshots

Dashboard

Agents Live Data

P&L Analysis

Pricing Simulation

Services

Service	Description	Port
Value UI	Web dashboard for monitoring and management	3000
Control Plane	REST API for configuration and data management	8200
Value Engine	Data processing pipelines and task orchestration	8000

Examples

Example	Description
basic_sync.py	Synchronous SDK usage
basic_async.py	Async SDK usage
gemini_instrumentation.py	Auto-instrument Gemini
pipeline_simulation.py	Full AI pipeline demo

See examples/ for more integration examples.

License

This repository contains components under different licenses:

• MIT: sdks/, examples/, seed-dummy-data/
• ELv2: value-control-plane-backend/, value-engine/, value-ui/

See LICENSE for details.