BeatAPI
BeatAPI is a capability layer for AI agents and applications: one API key provides access to lower-priced text, image, video, realtime, data, and workflow APIs. It standardizes model execution around inspectable contracts, task IDs, hosted outputs, usage records, webhooks, and retries.
At a Glance
- Indie developers and startups
- Product and engineering teams
- SaaS and application platforms
- Agent and automation builders
- +2 more
AI Tools by BeatAPI
(1)
JEV API — Developer Guide
Jev Decision Model API Guide
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Products & Services
A single API key and catalog for text/LLM, image, video, data APIs, workflows, and realtime capabilities. Developers inspect inputs, pricing, and execution mode, then call a supported capability through REST or MCP.
Synchronous or streamed text responses, including GPT-5.6-series access, tools, images, and reasoning controls through /v1/responses.
Asynchronous image-generation tasks for models such as Nano Banana, GPT Image, Seedream, and other catalog models, with polling/webhooks and hosted output.
Asynchronous video-generation tasks for models including Seedance, MiniMax H3, Veo, Kling, and others, with a common task lifecycle and hosted files.
Market Position
BeatAPI positions itself as a lower-priced, unified alternative to calling direct model providers or stitching together gateways such as OpenRouter, fal.ai, Replicate, WaveSpeedAI, and similar model-specific APIs. Its differentiators are one key across many capability types, a common task/status/output contract, hosted files, visible usage and failure records, and public price comparisons; the tradeoff is dependence on upstream providers rather than owning the underlying models.
Leadership
Founders
Eric Kang (Karmen)
The creator identifies as coming from an investment background and later leaving investment to write code and build products. He describes himself as a heavy AI-agent user and built BeatAPI after repeatedly wiring separate generation, data, MCP, and skills integrations into agent workflows. The BeatAPI blog uses the name Karmen; the associated public developer identity is Eric Kang.
Executive Team
Eric Kang (Karmen)
Founder and builder
Investment-background founder who moved into software development and product building; he describes personally using AI agents and building BeatAPI to solve his own multi-key, multi-provider workflow problems.
Founding Story
BeatAPI grew out of the founder's own agent workflow. Codex required a separate video-generation API, TikTok/Instagram data required additional access, and switching between Codex, Claude, OpenCode, and other runtimes meant rebuilding integrations and managing roughly 15–20 API keys. The initial vision was an all-in-one agent toolkit/capability layer that solves these integration problems with one key and a common execution surface.
Business Model
Revenue Model
Usage-based pricing and prepaid USD balance: customers pay for tokens, images, video seconds, workflow operations, and realtime usage. BeatAPI reserves/charges and settles or refunds usage according to task outcome; some catalog capabilities are free.
Pricing Tiers
Signup credit reaches 45 models; topping up any amount unlocks the full catalog.
Customers pay only for tokens, images, video, or workflow usage. Example: AI Ecommerce Video API is $0.30 per second for 1080p output.
jev-1.13-free works with a zero balance; before the first top-up, the account allows one successful request per minute.
Target Markets
- Indie developers and startups
- Product and engineering teams
- SaaS and application platforms
- Agent and automation builders
- Ecommerce and growth teams
- Creative and media-production teams
- AI agents needing model, tool, data, or workflow routing
- Image and video generation inside applications
- Ecommerce product ads, marketplace demos, landing-page videos, and creative-variant testing
- Music-video production workflows
- SaaS platforms that need to offer multiple AI models behind one customer-facing integration
- Agent automation and production pipelines requiring polling, webhooks, retries, idempotency, and hosted outputs