Pricing and revenue optimization
Models that set and adjust prices across thousands of combinations in real time, within the guardrails your team sets.
CUSTOM ML
Production ML, built for your domain.
Pricing, forecasting, computer vision, demand planning, optimization. These are the problems that call for a model trained on your data, for your constraints, and built to run reliably in production. We have shipped custom ML since 2016.
THE THESIS
Sometimes you can prompt your way there. Sometimes you need to train.
A frontier model with the right context, tools, and scaffolding handles a remarkable share of problems. When it does, that's the answer we'll point you to: faster to build, cheaper to run, and easier to change. Reaching for a custom model you don't need is its own kind of waste.
The expertise is knowing where that approach tops out, and where a model trained on your data starts to win. That line is what this page is about.
CHOOSING A MODEL
Pick the right model class, then customize only as much as needed.
Some problems need a frontier model. Some are better served by a smaller LLM that's cheaper, faster, or easier to control. Some need a fine-tuned or self-hosted model. Others need a purpose-built model trained against your objective. Match the class to the problem, then customize only as much as it demands.
GENERAL-PURPOSE LLMS
Best for language and reasoning
- Frontier models for the hardest reasoning, synthesis, ambiguity, and agentic work.
- Smaller models when the task is narrow, high-volume, or sensitive to latency and cost, and easier to constrain.
- Prompting, retrieval, tools, and evals get you there, with no training to maintain.
CUSTOM OR SELF-HOSTED LLMS
Best for control and adaptation
- Fine-tune or distill when you need behavior, format, or domain voice baked in.
- Self-host or deploy privately when data can't leave your environment, or you need latency, cost, and availability you control.
- You want to own the weights and decide when the model changes.
PURPOSE-BUILT ML MODELS
Best for prediction and optimization
- Prediction, ranking, forecasting, classification, perception, and optimization, where the answer is math.
- You need accuracy, calibration, latency, or cost a general model can't deliver at scale.
- Trained on your data against your objective, turning a proprietary edge into a durable advantage.
Most real systems mix more than one of these. The skill is matching each part to the right class and customizing only as much as it needs. We help you make those calls.
WHAT WE BUILD
Models for the problems that move your numbers.
Forecasting and demand planning
Demand, supply, churn, and capacity forecasts that hold up against real-world noise and feed the decisions downstream.
Computer vision
Detection, classification, and inspection on images, video, scans, and documents, at production accuracy and scale.
Recommendation and ranking
Search, recommendation, and matching tuned to your catalog and your customers, measured on the metrics you care about.
Optimization and operations research
Routing, scheduling, and allocation, the constrained problems where small gains compound into large ones.
Anomaly and risk detection
Models that catch fraud, defects, and drift early, so problems surface while they are still cheap to fix.
HOW IT FITS
Trained on your data. Wrapped in assurance.
Custom models run on the same foundation as everything else we build. They draw on your knowledge graph and data layer, and they sit inside the assurance and observability that keep production systems honest: evaluation against real outcomes, monitoring for drift, and the guardrails that catch a model going wrong before your customers do.
A model that was accurate at launch can degrade as the world changes. We track whether predictions hold up, retrain when they slip, and keep the model current with the business it serves.
How assurance works →SHIPPED WORK
Production results, measured.
$6M/week new revenue
Azul Airlines
Pricing, network, and marketing models. 8+ production ML systems running daily inside the airline's environment.
Read the case → 95% accuracy, ~5 weeks to ship
Global Shop Solutions
Document AI that turns messy invoices and vendor quotes into structured ERP data, cutting back-office overhead by 90%.
Read the case → MoveAgain neural decoders
Blackrock Neurotech
State-of-the-art neural decoders for a brain-computer interface that restores movement and communication.
Read the case →Some problems need a model of their own.
If the answer lives in your data and the gain is measured in revenue, cost, or accuracy, it's the kind of problem we've been solving since 2016. Tell us what you're trying to move.
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