Audience
AI startups, voice AI companies, autonomous agent builders, LLM application developers, CTOs and AI engineers building agent-based products
About Paygent
Paygent is the monetization and cost-tracking infrastructure platform built for AI-native businesses. Unlike legacy billing tools that only track revenue, Paygent gives AI companies real-time visibility into margins, infrastructure costs, and profitability per customer and per agent workflow.
AI companies today operate across fragmented LLM providers, APIs, and cloud infrastructure, making it difficult to understand true unit economics. Teams often scale usage without realizing margins are shrinking.
Paygent solves this by unifying real-time AI infrastructure cost attribution and automated billing into one platform. It tracks every LLM call, API request, and compute event tied to agent workflows, enabling customer-level gross profit visibility, automated billing, predictive pricing simulation, and cost alerts to prevent runaway agent loops.
Built for AI startups, voice AI platforms, and autonomous agent teams, Paygent offers native SDKs for Node.js, Python, and Go.
Pricing
Starter ($399/month) - 10M events, 7 year retention, 24/7 priority support
Growth ($799/month) - 25M events, 7 year retention, 24/7 priority support
Enterprise (Custom) - unlimited events, custom integrations, dedicated support
Company Information
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Product Details
Paygent Frequently Asked Questions
Paygent Product Features
Paygent Verified User Reviews
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Probability You Would Recommend?1 2 3 4 5 6 7 8 9 10
"Great tool to manage agent monetization" Edited 2026-05-13
Pros: * Granular "Node-Level" Observability:
Unlike Stripe, which sees a single monthly API bill, Paygent tracks costs at the graph node level. This allows you to pinpoint exactly which tool_call or llm_node is burning your budget.
* Real-Time Margin Protection:
It calculates the delta between what you charge a user and what the inference actually costs in milliseconds. If a recursive loop in your LangGraph starts eating your margin, Paygent can trigger an automated "circuit breaker" to pause the agent.
* Vendor Agnostic Comparison:
It normalizes billing data across OpenAI, Anthropic, and local models. You can see in real-time if switching a specific node from GPT-4o to Claude 3.5 Sonnet actually improves your unit economics.
* Plug-and-Play for Agentic Frameworks:
Paygent offers native SDKs for LangChain and LangGraph, meaning you don't have to write custom middleware to "tag" your metadata for billing; the infrastructure does it for you.Cons: The granular instrumentation required for a 50-node graph introduces a higher level of architectural complexity and a critical dependency on real-time financial telemetry that demands disciplined engineering oversight.
Overall: We run a high-scale LangGraph implementation with over 50 nodes and multiple LLM providers. Our biggest headache was the 'black box' monthly bill; we knew we were spending a lot, but we couldn't see where the leak was.
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Integrating Paygent changed everything. We moved from aggregated billing to granular, node-level tracking. Within the first month, we identified specific 'culprit nodes' that were driving 40% of our costs through inefficient retries and expensive model fallbacks. The dashboard makes it incredibly easy to compare spend across different agents and providers in real-time. If you’re serious about scaling AI without losing control of your margins, Paygent is a must-have." -
Probability You Would Recommend?1 2 3 4 5 6 7 8 9 10
"Great Founders To Work With " Posted 2026-05-11
Pros: The founders are very responsive in solving real-time issues, and the feedback is seriously taken.
Cons: I hope we can move from their growth pro plan to enterprise at a slightly discounted rate, haha
Overall: Cost optimisation was imp for us tbh, and they came on time
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