apiegg is a server-side LLM router for AI agents. Point any agent at one endpoint and apiegg reads each request — tools, context, intent — and routes it to the best-fit model, instantly. No model lists. No babysitting. No code changes.
✨ Free during early access · no credit card · see pricing
Three things apiegg does on every single request — so you never think about model choice again.
Every call gets inspected — tool signatures, payload size, message patterns, client fingerprint — and matched to the best-fit model. Frontier muscle when the task is hard, fast & cheap when it isn't. Explicit model pins are always honored.
Malformed tool calls murder agent runs at 3am. apiegg validates every tool-call response and auto-heals broken JSON before it ever reaches your agent. Reliability is a routing feature.
Stop paying frontier prices for "summarize this." Difficulty-based matching sends trivial turns to cheap-and-fast models automatically. Your bill drops while your agents get faster.
apiegg learns from real outcomes — which routes finished the task, which flopped — and keeps refining its routing. The map is not the moat. The map-making is.
Every project deserves a different amount of brain.
example taskday-to-day agent work, refactors
Tell apiegg how much brain each project deserves — the router handles the rest.
Every request analyzed, balanced and routed in milliseconds. Here's what that looks like.
Switch week 1. Same workload, same agents — the router sends each turn to a model that's cheap enough and smart enough.
Grey = before. Gold = after. Same tasks, right-sized models.
*All dashboard figures are illustrative demos — real numbers replace them at launch.
If it speaks OpenAI or Anthropic, it speaks apiegg. Point your baseUrl at us — zero code changes.
/v1/chat/completions · any SDK, any client/v1/messages · native agent tooling welcomeexport OPENAI_BASE_URL=https://api.apiegg.com/v1
export OPENAI_API_KEY=egg_•••••export ANTHROPIC_BASE_URL=https://api.apiegg.com
export ANTHROPIC_API_KEY=egg_•••••That's it. Same code, same SDKs — new intelligence underneath.
…and any script that can hit an OpenAI-style endpoint. If yours is missing, it probably still works — tell us about it.
What early riders say after pointing their fleets at one endpoint.
I deleted my model-picker config the same afternoon. The bill dropped, the runs got faster — and honestly, I don't miss choosing.
The auto-healing alone is worth it. Half my crashes were malformed tool calls — now I don't even see them in the logs.
We stopped arguing about which model to use for what. The router just handles it, and the team ships features instead.
Gateways translate formats — you still pick the model for every call. apiegg decides. It analyzes each request (tools, context size, message patterns) and routes it to the best-fit model, heals malformed tool calls, and learns from outcomes. You point your client once and never touch model config again.
Dozens behind one endpoint — frontier reasoners, fast-and-cheap workhorses, long-context readers, and tool-call specialists — with more added continuously. You never pick from the menu yourself, but you always can: explicit model pins are honored 100% of the time.
Almost certainly. apiegg speaks two dialects natively — the OpenAI API format and the Anthropic API format. If your tool lets you set a base URL (OpenClaw, Claude Code, Cursor, Aider, LangChain…), you point it at apiegg, paste your key, done. Zero code changes.
Three safety nets. One: pin any request or client to a specific model and apiegg obeys, always. Two: malformed tool-call responses are validated and auto-healed before they can crash your run. Three: the outcome feedback loop means a bad route is a lesson, not a habit — routing quality compounds over time.
Most agent workloads are lopsided: a few hard turns buried in a mountain of trivial ones — yet everything gets routed to an expensive default. apiegg matches task difficulty to model price per request. In our own fleet testing that trimmed up to 60% off spend. Same output quality, right-sized engines.
apiegg is built privacy-first. Requests are processed to route them and improve routing — your data is never used to train models, and full data-handling policy ships with the docs at launch. Questions before then? Ask us directly.
Free usage during the pilot, founding-user pricing forever, a direct line to the founders, and genuine influence over the roadmap. We're building this with agent developers, not just for them.
Point your agents at one endpoint and never think about model choice again. Dozens of models, two API dialects, zero config to maintain.
✨ Free during early access · no credit card · your agents will thank you
Last year I was running a small fleet of AI agents — coding helpers, research assistants, little ops bots. And every night, one of them would pick a dumb fight with the wrong model: a frontier brain for "summarize this," a bargain brain for a gnarly refactor. Slow runs. Bloated bills. Me, babysitting model pickers at 2am instead of shipping.
So we built the router we always wanted. One endpoint that reads each request — the tools it wants, the context it carries, the pattern it's stuck in — and hatches the right model for that exact turn. The first week we pointed it at our own fleet, our spend nearly halved and the 3am crashes went quiet.
And it wasn't only model choice. When a couple of endpoints got slow or went dark, everything downstream crawled with them — every agent, every pipeline, hostage to a bottleneck we couldn't even see. So apiegg watches endpoint health too, and routes around trouble before your run ever feels it.
Here's the thing we learned along the way: the map is not the moat — the map-making is. Every call routed, every outcome observed, apiegg gets a little sharper. It's a router that compounds.
If you're building agents, I'd love for you to kick the tires early and tell us what breaks. That's the deal.
— Kazi, founder