Compass is the first model selection engine that balances cost against real business KPIs — so you spend less where outcomes don't suffer, and invest more where they matter most.
Teams either overspend by defaulting to the most expensive model for everything, or cut cost blindly and watch quality metrics drop — with no systematic way to find the right balance.
Compass doesn't just cut cost — it finds the optimal tradeoff between what you spend and the business outcomes you get. Less where quality doesn't suffer, more where it matters.
Drop in our SDK or use the OpenAI-compatible API. Point your LLM calls through Compass. Define the KPIs that matter to your business.
Compass intelligently distributes traffic across models, running controlled experiments to learn which models drive the best business outcomes for each request type.
As KPI telemetry flows back, Compass converges on optimal selection policies per workflow. It continuously adapts as models improve and your product evolves.
A continuous feedback loop between model decisions and business outcomes — fully automated.
Compass was born from a pattern we recognized across two seemingly different domains.
Co-founder Alex spent years building ad optimization engines for Return on Ad Spend (ROAS) campaigns. The breakthrough insight: ad platforms that optimized only on click-through rates and impressions consistently underperformed those that closed the loop with actual business outcomes — revenue, customer lifetime value, margin per acquisition.
The ad industry spent years to shift away from pure technical metrics (CTR, CPM) that are easy to measure but often misleading. The campaigns that actually moved the needle were the ones where ad telemetry was blended with downstream business data — creating a closed feedback loop that could learn what "good" really meant for each customer.
Today's LLM model selection typically relies on token cost, latency, and benchmark quality scores — proxies that are easy to measure but don't capture what matters downstream. The model that scores highest on a benchmark isn't necessarily the model that closes more tickets, converts more leads, or reduces churn. Compass brings the same closed-loop approach to model selection that transformed ad optimization.
Compass learns the right model for each one — automatically.
Send complex billing issues to frontier models, simple FAQs to fast/cheap models. Optimize for CSAT and resolution time.
KPI: CSAT + Escalation RateMaximize reply rates and meeting bookings by learning which models generate the most effective personalized messaging.
KPI: Reply Rate + Meetings BookedBalance creative quality with production speed. Compass learns which models produce content that drives the most engagement.
KPI: Engagement + Publish RateOptimize retrieval-augmented generation for answer accuracy and user satisfaction across different query complexity levels.
KPI: Answer Accuracy + Click-throughDirect sensitive regulatory content to models with the lowest error rates while keeping costs manageable for routine checks.
KPI: Error Rate + Processing TimeIncrease conversion by learning which models generate the most compelling product suggestions for each customer segment.
KPI: Conversion Rate + AOVJoin our early access program. Compass finds the optimal balance between model cost and business outcomes — automatically.