Bespoke AI builds for problems no off-the-shelf tool solves. Product matching, demand forecasting, multilingual support, intelligent triage, scoped per project.
Off-the-shelf AI tools cover the common ecommerce use cases reasonably well: chatbots, generic content generation, basic image processing. But every brand has at least one operational problem that those tools cannot solve at the quality bar required. A jewelry brand needs visual product matching against customer-submitted reference photos. A multi-brand retailer needs demand forecasting that accounts for regional preferences. A bilingual store needs customer-support summarization in two languages with consistent voice. A high-velocity dropshipper needs supplier-quality scoring across millions of SKUs. These are not problems an AI starter pack solves. They are problems we scope, design, build, train, and operate on a per-project basis.
Everything in this service
Structured discovery to define the AI problem precisely: what input is available, what output is required, what counts as success, what is the human-baseline performance, and what budget the build can sustain.
Selection of the right model approach (zero-shot prompting, few-shot, fine-tuning, RAG, custom training, or hybrid) based on the problem characteristics. Cost and latency forecasted before any build.
Implementation in your preferred infrastructure (your AWS, our hosting, or hybrid). Training data curated and labeled where required. Evaluation pipeline built before model goes live.
Every custom AI build comes with a documented evaluation suite: accuracy, precision, recall, latency, cost per inference. Baselines tracked over time. Regression alerts if model performance degrades.
API endpoints, queue workers, or batch jobs depending on use case. Authentication, rate limiting, error handling, and monitoring configured. Model version pinning and rollback capability.
Monthly model review covering accuracy, cost trajectory, and emerging failure modes. Retraining cycles scheduled where needed. New model versions evaluated and rolled out with confidence intervals.
Custom AI is justified when off-the-shelf tools either cannot solve the problem at all, or solve it poorly enough that the cost of running them outweighs the value delivered. The economic case is clear when you compare the labor cost of doing the work manually (or the lost-opportunity cost of not doing it) against the build cost plus ongoing inference cost. We have built custom AI for product matching, demand forecasting, intelligent customer triage, supplier scoring, ad-creative classification, fraud detection, and multilingual content generation, each justified by a clear ROI case before the project started.
Two-hour structured session to define the problem, the data available, the required output, and the human-baseline performance. We tell you on this call whether AI is the right answer or whether something simpler would work.
Architecture document covering model approach, infrastructure requirements, training data needs, ongoing inference cost forecast, and fixed-price quote for the build.
Iterative build with evaluation milestones every 2 weeks. You see model performance metrics throughout the build, not just at the end.
Production deployment, monitoring configured, documentation handed over. Optional ongoing operations retainer or we hand off to your engineering team with full handover.
Book a free 30-minute call and walk us through the AI problem you have not been able to solve with off-the-shelf tools. We will tell you whether it is buildable, what it would cost, and what ROI looks like.