Visibility
Comprehensive analytics on spend, usage, and model mix — per team and per employee. Stop flying blind.
Token Resources
The continual learning layer for your AI traffic.
In the future, companies will be meta-learning algorithms operating over their token streams. Today they discard that traffic the moment a response returns. We capture every query/response pair through a drop-in proxy, store it on your infrastructure, and turn it into smart routing, savings, and backtesting.
How it flows
Every request, captured on its way to the model.
Your team's requests fan out to many providers. We intercept them in the hot path, store the full history on your own infrastructure, and feed it back as continual learning.
The problem
You're overpaying for inference and throwing away your best AI asset.
A 50-person team running 1M tokens/employee/month spends roughly $250K–$1M/year on frontier model access — with near-zero visibility into where that spend goes, which queries drive it, or whether a cheaper model would have answered just as well.
That same traffic is a proprietary dataset that captures how your business actually works. Today it is discarded the moment a response is returned.
The result: enterprises overpay for inference, fly blind on usage, and throw away their most valuable AI asset.
The solution
Capture it. Keep it. Act on it.
Capture is a drop-in proxy — an OpenAI/Anthropic-compatible endpoint. One config change, no application rewrites. An SDK and network-level option exist for teams that want them.
Savings
Smart model-routing recommendations and local response caching that cut token spend without quality loss.
Optimization
Backtest candidate model changes against your real historical traffic before you roll them out.
Hybrid routing
Sensitivity-aware routing between local and frontier models. Sensitive queries never leave the perimeter; cheap queries never hit a frontier bill.
On data control
Your traffic never enters our perimeter.
Enterprises buy Zero Data Retention from providers precisely because their traffic is sensitive. We are not the inverse of that — we are how you keep it.
Storage is on-prem (or in your own cloud tenant) by default. We never hold your data.
This is for you if
You feel the token bill every month.
We're built for high-intensity teams where model choice, caching, and routing actually move the number.
heavy users of AI tools
Engineers, analysts, and agents leaning on frontier models as part of their daily workflow.
tokens / user / month
Usage intense enough that smarter routing and local caching cut a real line item, not a rounding error.
annual token budget
Frontier-model spend large enough that visibility and savings pay for themselves in the first quarter.
Why now
The routing lever just became real.
Token consumption is projected to grow ~24× by 2030 — to roughly 120 quadrillion tokens/month — per Goldman Sachs, with enterprise/agentic adoption leading the surge. The cost and data-capture problem grows with it.
Models converged
The set of models within range of SOTA has widened sharply over the last six months — routing between them is now a real lever, not a rounding error.
Access is tightening
Providers are constraining access to top-tier models. Enterprises can no longer assume one provider covers everything — they must plan for a hybrid, multi-model future, which requires a routing layer.
The team
We are the best in the world at intercepting and routing requests.
Capturing traffic in the hot path, deciding in single-digit milliseconds, and never dropping a request is the same systems problem as a high-frequency trading engine — and we have built exactly that, at scale.
$1T+
traded in 2021 on systems we built
2 PB
datacenter built for machine-learning trading models
<10 ms
routing decisions made in the hot path
Low-latency systems
ML infrastructure
Market-data capture
Quant routing
Why not the incumbents
Nobody else is positioned to sit in the hot path and host your data.
Model providers
Anthropic, OpenAI, Google are conflicted — routing customers away from their own models is against their interest.
Model routers
OpenRouter and peers are marketplaces. They are not positioned to host proprietary traffic, on-prem storage, or backtesting. The system of record sits above the marketplace.
Observability players
Datadog, Arize, Langfuse offer visibility but do not sit in the hot path and act — route, cache, fail over — on the traffic.
Conversation capture
Gong proves that "capture discarded traffic, make it an asset" is valuable — but they are committed to the sales-call vertical and SaaS-cloud storage.
The opportunity: provider neutrality, sitting in the hot path, on-prem by default.
Design partners
Win the most paranoid buyer first.
We're signing three design partners — high-intensity teams of 10–100 running 1M+ tokens/employee/month. Free during the design-partner period in exchange for deployment access and a reference. We retain no rights to your data.
- Measurable token savings
- Learnings your team loves
- On-prem by default — your data stays yours