Developers are locked into single providers who throttle or ban usage, and manually switching between models (Claude, GPT, Chinese models) is painful
A drop-in proxy that routes coding agent requests to the optimal model based on task type, cost budget, and provider availability - automatically falls back when one provider is degraded or rate-limited
Usage-based pricing with a small markup on API passthrough, plus subscription tiers for routing intelligence and team features
The pain signals are visceral and real — developers literally switching providers mid-task, dealing with degraded quality, HTTP errors, and rate limits daily. 917 HN upvotes confirms widespread frustration. This isn't a nice-to-have; it's blocking actual work output for power users spending $200-2000+/month on AI APIs.
TAM for LLM API routing is estimated at $2-5B by 2027 as enterprise AI spend grows. The code-agent-specific niche is smaller but growing fast — likely 500K-2M power developers globally spending significant amounts on AI coding tools. At $20-100/month premium, that's a $120M-$2.4B addressable market. Not massive yet, but growing 3-5x annually.
These users already pay $20-200/month for AI tools and hundreds more for direct API access. A routing layer that saves money AND improves reliability has a clear ROI pitch. However, the margin on API passthrough is thin (OpenRouter proves ~10-20% markup is tolerable). The premium must come from intelligence/reliability, not just proxying. Some resistance expected from developers who prefer DIY/open-source (LiteLLM exists).
A basic proxy with fallback routing is straightforward — 2-3 weeks for a solo dev. But the DIFFERENTIATOR (intelligent task-aware routing for code agents) is genuinely hard. You need: prompt classification, quality benchmarking across models for coding tasks, real-time provider health monitoring, cost optimization algorithms, and low-latency proxy infrastructure. An MVP with basic smart routing is doable in 6-8 weeks, but the intelligence layer that beats LiteLLM/OpenRouter takes real ML work and data collection.
OpenRouter and LiteLLM are well-established and cover 70% of the use case (unified API, fallbacks). The gap is specifically in INTELLIGENT routing for CODE tasks — no one does this well yet. But the gap is narrower than it looks: OpenRouter could add task-aware routing, Martian could specialize for code, and Portkey could add ML-based routing. Your moat is thin unless you build proprietary data on code-task-to-model-quality mappings quickly. First-mover advantage matters here but isn't durable alone.
This is inherently recurring — developers use coding agents daily and the routing layer sits in their critical path. Usage-based revenue naturally recurs and grows with adoption. Once integrated into a team's workflow (CI/CD, agent configs), switching costs are moderate. The subscription for routing intelligence and analytics adds predictable MRR on top of usage revenue.
- +Acute, validated pain point with strong signal (917 HN upvotes, visceral user quotes)
- +Code-agent-specific routing is an unoccupied niche — no competitor optimizes for this workflow
- +Inherently sticky and recurring — sits in the developer's daily critical path
- +Multi-provider resilience is becoming more important as providers impose stricter limits
- +Usage-based model aligns revenue with value delivered — customers pay more as they get more value
- !OpenRouter or LiteLLM adds intelligent code-aware routing and kills your differentiation overnight — they have distribution you don't
- !Thin margins on API passthrough mean you need significant volume or strong premium features to build a real business
- !Provider API terms may prohibit or complicate proxying — Anthropic and OpenAI have changed ToS before
- !The market may consolidate around 1-2 dominant providers, reducing the need for multi-provider routing
- !Building truly intelligent routing requires expensive data collection and ML iteration — easy to underestimate
Unified API gateway that provides access to 200+ models from multiple providers
Open-source proxy/SDK that provides a unified interface to 100+ LLM providers. Acts as a drop-in replacement with OpenAI-compatible format, with load balancing and fallback support
AI-powered model router that uses a trained classifier to pick the best model for each prompt based on quality, cost, and latency tradeoffs
AI gateway and observability platform for LLM apps. Provides unified API, automatic retries, fallbacks, load balancing, caching, and detailed analytics across providers
LLM routing platform that benchmarks models across tasks and routes requests to the optimal model based on quality, cost, and speed preferences
OpenAI-compatible proxy server that: (1) accepts requests from popular coding agents (Claude Code, Aider, Cursor-compatible), (2) monitors provider health and rate limits in real-time, (3) auto-falls back across 3-4 providers (Anthropic, OpenAI, DeepSeek, Google) with zero config, (4) classifies tasks as simple/complex using heuristics (prompt length, file count, error context) and routes cheap tasks to cheaper models. Ship as a single Docker container or hosted service. Skip the ML-based routing for v1 — use rule-based heuristics that you can tune manually based on user feedback.
Free tier: 1000 requests/month with basic fallback routing → Pro ($29/month): unlimited routing, cost analytics dashboard, team API key management → Usage markup: 5-10% on all API passthrough → Enterprise ($199+/month): custom routing rules, SLA guarantees, SSO, audit logs, dedicated support. Target $5-15 ARPU blended across free and paid users.
4-6 weeks to MVP with usage-based pricing live. First paying users within 1-2 weeks of launch if you target the HN/developer community that's already complaining about this problem. $1K MRR achievable within 2-3 months with aggressive community marketing. $10K MRR is the hard part — requires either enterprise deals or viral adoption among coding agent power users.
- “forcefully cutting myself over to one of the alternative Chinese models to just get over the hump”
- “normalise API pricing at a sensible rate with sensible semantics”
- “Dealing with Claude going into stupid mode 15 times a day, constant HTTP errors”
- “capacity constrained so is having to make choices about the customers they want to serve”