We help Ecommerce & Retail teams put predictive models into production. Predictive LTV and propensity for smarter bidding and segmentation.
An ads agency and an email agency will never share a customer view.
Predictive LTV and propensity for smarter bidding and segmentation.
One warehouse-native architecture where the same enriched data feeds paid, lifecycle and the storefront. Server-side tracking and identity resolution produce a single customer view in BigQuery. That view feeds enriched segments back into the ad platforms, and the same data drives the email and SMS flows — so paid and lifecycle compound instead of competing.
Artificial intelligence only counts when it runs in production, changes what your team does next, and shows up in revenue you can measure against a clear baseline. Everything else is expensive theater.
Scoring and recommendations, plus any model where a data problem is attached to revenue. Lead scoring, churn propensity, lifetime value, and demand forecasting trained on your closed-won history, plus catalog-trained recommendations that raise order value. Every use case is backtested against your own history before you pay.
Your own language models, grounded in your data, running in your cloud. Internal LLMs and retrieval pipelines over your documents, knowledge base, and warehouse, powering search, drafting, and answers your team can trust. Your data stays inside your environment, behind your access controls.
RAG, fine-tuning, or both, chosen on the evidence and tuned to your domain. Retrieval-augmented generation when your knowledge changes daily, fine-tuning when a model must internalize your tone and judgment, and often both. Every tuned model is versioned and scored against a held-out set, so accuracy is a number you can see.
Sentiment, transcription, and classification across text, media, and calls. Pipelines that classify tickets, reviews, calls, and leads, score sentiment, and route what matters to the right owner. Speech-to-text, video understanding, and image analysis turn unstructured media into structured signal in your dashboards.
We audit your data and rank every candidate use case by revenue at stake. You get a scored roadmap with one clear first build.
We build the pipelines, labels, and clean training sets the first use case needs. This is the step most vendors skip, and the one most failed projects trace back to.
Every model is backtested against your own history and a baseline it has to beat. If it cannot win, it does not ship.
Models deploy inside your stack, so scores and recommendations show up where your team already works. Monitored from day one.
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