TTU — Inference Intelligence Platform
TTU Router measures model quality on each response and optimizes routing adaptively. The difference between reading the exam questions and reading the answers. Provider-agnostic, with inspectable decision trails for every routing decision.
Routing happens before the answer exists
Organizations send thousands of AI requests daily. Every response reaches an end user, a customer, patient, or employee, without anyone measuring whether the model was confident in its answer. Every query costs the same regardless of difficulty. And provider updates can change answer quality without warning.
Existing routing solutions analyze the question and make a qualified guess about which model is needed. They solve parts of the cost problem but nothing of the quality or visibility problem. They never measure the response.
Response-aware inference intelligence
The design principle: separate measurement (AI-driven, adaptive) from decision (deterministic, inspectable, reproducible). The measurement is intelligent. The decision trail is predictable and auditable.
Response-aware routing
Each response is assessed individually using a proprietary quality estimation method. Routing adapts to actual difficulty, not predicted difficulty. The routing decision is based on the answer, not a prediction about the question.
Multi-tier cascade routing
Progressive escalation across multiple model tiers, not just binary small/large routing. Simple queries stay in the first tier, complex queries escalate through progressively more capable models. Verified to achieve higher quality than binary routing.
Consistency routing
For batch and agentic workloads: multiple independent generations compared for agreement. Verified to exceed single-model quality, intelligent routing can be better than always using the most expensive model.
Safety routing
Queries in sensitive domains (medical, legal, financial) are handled with higher safety requirements automatically. Domain detection with dedicated quality thresholds per domain.
Budget control per session
Set a cost cap per session. TTU distributes the budget intelligently across the session's lifetime, allocating the expensive model where it matters most and saving on simpler questions.
Shadow mode
Run TTU alongside your existing flow with zero risk. No responses are affected. You get full quality visibility, cost analysis, and a routing performance audit of your current setup before making any changes.
The position is empty
Existing inference routing solutions, including API gateways, open-source proxies, and observability platforms, let users or rules select models. Quality measurement on the actual response, inspectable decision trails, and connection to output verification are missing from existing routing solutions.
| Approach | How it works | Assesses response? |
|---|---|---|
| API gateways | Multi-provider proxy, user selects model | No |
| Open-source proxies | Unified API layer with routing rules | No |
| Observability platforms | Logging, monitoring, cost tracking | No |
| Provider auto-routing | Vendor-native model selection | Partial, own models only |
| TTU | Response-aware routing + safety + cascade | Yes |
From routing to inference governance
Today: Intelligent routing
Response-aware cost optimization. Multi-tier cascade routing. Consistency routing for batch workloads. Safety routing for sensitive domains. Shadow mode for risk-free evaluation. Budget control per session. Verified output-verification integration.
Next: Decision intelligence
Decision Engine with four outcomes: deliver, escalate, ask for clarification, or hand off to a human, because sometimes AI should not answer at all. Multi-provider verification. Quality overlay for organizations with existing routing. Fabrication detection integrated as an additional quality signal, working on any model via standard API. Monotonic calibration designed to never degrade routing quality.
Vision: Inference governance platform
Model Quality Index aggregated across customers for early detection of provider changes. Automatic model improvement from escalation data. Compliance routing per jurisdiction with structured decision artifacts for audit. Fleet governance across all of an organization's AI systems. The control plane for AI inference.
TTU Router — Common questions
How does TTU reduce inference costs?
TTU sits as a proxy between your application and AI providers. It measures quality on each response and routes simple queries to efficient models while escalating complex ones. Routing adapts to actual difficulty, not predicted difficulty.
What makes TTU different from other routing solutions?
Existing solutions let users or rules select models. TTU measures quality on each individual response. It also provides safety routing for sensitive domains, cascade routing across multiple tiers, and an inspectable decision trail for every routing decision.