Infrastructure pillar

Control token burn
before it becomes structural

LLM gateways route requests. Vertical AI teams need more: workflow-level cost attribution, routing policies that pick the cheapest capable model per step, and margin guardrails before inference spend compounds with every active user.

The problem

API bills scale faster than revenue

Most teams discover LLM cost pain after launch. Blended cloud invoices hide which workflows burn tokens. Premium models applied uniformly turn inference from COGS into a structural liability.

01

No workflow attribution

You see total API spend, not cost per detection, per report, per RAG query. Optimization is guesswork.

02

Routing as afterthought

Model selection lives in app code. Failover upgrades models without finance knowing.

03

Margin blind spots

User-facing credits decouple from real inference cost. Gross margin erodes before dashboards catch it.

Capabilities

Cost engine + routing policy in one layer

ozDNA is vertical AI infrastructure with a first-class cost engine: attribute every call to workflow and account, enforce routing policies per step, and connect usage economics to production models.

01

Workflow-level attribution

Map tokens and dollars to named workflows — detection, retrieval, generation, re-ranking — not just API keys.

02

Cheapest capable model routing

LLM routing policies per vertical step: which model clears your quality bar at lowest cost and acceptable latency?

03

Margin guardrails

Tie user credits to real spend. Alert and throttle before a single workflow destroys unit economics.

Operating model

Three steps to measurable inference cost

  1. Instrument — Name workflows and attach cost tags to every LLM call.
  2. Route — Define per-step model policies; stop paying frontier prices for bulk tasks.
  3. Govern — Review cost per outcome weekly; adjust routing before bills become structural.

Platform architecture →

GPU Bill Bodyguard

Cost control in practice

Evaluating gateways

Routing proxies vs vertical AI infrastructure

Gateways route requests; ozDNA adds RAG governance + cost optimization for vertical AI products in production.

Built on ozDNA

Production vertical AI proof

TezMakale and ComplyDNA run on this infrastructure today.

Case study

Stop guessing inference cost

Join ozDNA early access. We will map your workflows, routing rules, and margin targets onto the cost engine.

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