The Applied AI Lab for Advertising Technology

TensorLabs

Where machine intelligence meets the bid stream.

We partner with publishers, SSPs, and DSPs to build custom ML systems that move the metrics that matter.

50B+
Bid requests optimized monthly
<5ms
Model inference latency
6
Published research papers
3
Engagement models
Our Approach

Precision-Engineered AI,
Not Off-the-Shelf Models

Every auction environment is unique — shaped by its supply composition, bidder behavior, and latency constraints. Generic ML fails here. We build AI systems that understand these dynamics from the ground up.

We sit at the intersection of applied research and production engineering: publish what we discover, deploy what we prove, and transfer the capability so your team owns the outcome.

01

Domain-Native Models

Every model is trained on your data, for your auction environment. We don't retrofit general-purpose AI — we build from first principles.

02

Production-First Engineering

Research that can't survive sub-10ms latency constraints never leaves the lab. Our systems are built for the bid stream from day one.

03

Full Knowledge Transfer

We don't create dependencies. Every engagement ends with your team owning the models, the pipeline, and the methodology.

04

Research-Backed Decisions

Our published work isn't marketing — it's the foundation of every system we build. We share our methods because rigor is our advantage.

Solutions

Engineered for the Bid Stream

From optimization engines to agentic systems — built for your stack and auction environment.

Core Optimization

Production-grade ML systems for the foundational problems of programmatic advertising — pricing, routing, scoring, pacing, and fraud.

Floor Price Optimization
Dynamic price floors that maximize publisher yield in real time using gradient-boosted models trained on auction outcomes.
Supply Path Optimization
Intelligent routing that cuts intermediary hops, reduces fees, and boosts win rates through learned bidder quality scores.
Traffic Ranking
ML-driven impression scoring to prioritize high-value traffic at scale, before it reaches the auction.
Budget Pacing
Adaptive spend algorithms calibrated against temporal bidder behavior patterns to hit campaign goals precisely.
Fraud Prevention
Multi-signal detection models that identify invalid traffic patterns before a single dollar is wasted.

The Agentic Lab

Next-generation autonomous systems that reason, negotiate, and optimize across the full advertising lifecycle.

Agentic Media Buying
Autonomous agents that negotiate, bid, and optimize campaigns end-to-end — reducing human overhead while improving outcomes.
LLM2RTB
Large language models fine-tuned for high-speed OpenRTB request generation, bridging natural language intent and programmatic execution.

Cloud ML Infrastructure

The platform layer that makes ad tech ML possible at scale — from training pipelines to sub-millisecond serving.

MLOps for Ad Tech
Production pipelines purpose-built for bidding latency constraints, with automated retraining and drift detection.
Cost Reduction
Right-sized inference, smart caching, and workload scheduling that typically cut cloud ML spend by 30-50%.
Low-Latency Serving
Sub-10ms model inference at the edge for real-time decisioning, with graceful degradation under load.
How We Work

Engagement Models

The right team at the right stage — matched to your organization's ambitions.

Rapid-Impact Intervention

SWAT Team

A high-impact, multidisciplinary strike force that hits the ground running. We diagnose performance bottlenecks, architect the solution, and deliver measurable lift within weeks.

End-to-end diagnostic and solution delivery
Cross-functional teams: ML engineers, infra, and ad tech strategists
Measurable KPI improvement with defined timelines
Typical timeline: 4-8 weeksLearn more
Applied Research Partnership

The ML Lab

A dedicated research partnership where our scientists and engineers co-develop proprietary models alongside your team — from initial hypothesis through production deployment.

Joint model development and full knowledge transfer
Custom algorithms built on your data and objectives
Structured engagement from discovery to production scale
Typical timeline: 3-6 monthsLearn more
Risk-Free Experimentation

Simulator

A controlled experimentation environment purpose-built for programmatic advertising. Test strategies against realistic auction dynamics before a single dollar touches live traffic.

Realistic auction simulation with historical data replay
A/B scenario testing for pricing, pacing, and bidding logic
Quantified impact forecasting before production rollout
Typical timeline: 2-4 weeksLearn more
From the Lab

Latest Research

View all publications

Ready to build?

No pitch decks, no generic demos — just a technical conversation about your data and your goals.

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