Ad tech
Specialists inside the RTB auction window.
The IAB OpenRTB spec allows 100 milliseconds end-to-end. Frontier API calls arrive too late to influence the bid. A domain-specialist model running on your own hardware completes brand-safety, bid-shading, and MFA classification comfortably within the auction envelope, at zero marginal cost per decision.
Why a specialist model
Three reasons frontier models do not fit.
- Frontier API latency exceeds the auction window
- The IAB OpenRTB spec allows 100ms end-to-end. A frontier API round-trip adds 200 to 500ms before a response arrives. A small specialist model on your own hardware fits the auction envelope; a frontier API does not.
- Per-decision cost is prohibitive at auction scale
- Running hundreds of millions of daily bid requests through a frontier API at commercial rates costs more than the CPM on most inventory. A specialist on owned hardware converts a variable per-token cost into a fixed infrastructure cost that scales to zero at the margin.
- Bid logic must not leave your network
- Your blocklist weights, brand-safety thresholds, and shading coefficients are core IP. Sending bid-request payloads to a third-party API exposes that logic and creates a data-egress record that complicates buyer and publisher contracts.
Use cases
Concrete workflows, not a category claim.
Each use case below maps to a real workflow a design-partner team would bring to Modelsmith. The specialist model is trained on your data, evaluated against your rubric, and promoted through your governance gate.
Brand-safety classification
Train a specialist to score inventory against your IAB-based blocklist using page context, URL, and creative-adjacency signals. Human reviewers set the thresholds; the model enforces them at scale without per-call cost.
Bid shading
Fine-tune a specialist on your historical win and loss data to predict the optimal clearing price below the first-price ceiling. The model adapts to shifting auction dynamics rather than reading from a static lookup table.
Pre-bid MFA filtering
Classify made-for-advertising inventory before the bid is placed. Train on your own MFA-labelled dataset so the model reflects your definition of quality, not a third-party taxonomy imposed at the exchange.
On-device gaming SDK
A sub-4B specialist embedded in a mobile gaming SDK for contextual ad placement. No network call required; classification runs on the device with no user data leaving the handset.
Get started
Bring a ad tech workflow to the design-partner cohort.
Apply to the design-partner programme with your workflow in mind. We will scope the Synthetic POC together, run a complete specialisation cycle on synthetic domain scenarios, and hand you a validated model with a full evidence bundle before any licence commitment.