FAQ
Common questions
We build AI features as scalable microservices designed to handle your current load and grow with you. Whether you serve hundreds or millions of users, the architecture supports elastic scaling.
Yes. We commonly embed with client engineering teams, working within your existing codebase, CI/CD pipelines, and development processes. Knowledge transfer is part of every engagement.
We build automated retraining pipelines that keep models current as your data evolves. We also provide monitoring dashboards that track model performance and alert your team to accuracy degradation.
We optimize for sub-200ms response times for real-time features like search and copilots. Batch processing features like analytics and predictions run on schedules that balance freshness with compute costs.
See where AI cuts cost in your business.
Book a free 20-minute call: tell us the workflow that costs you most and we'll tell you, honestly, whether AI fixes it and what it would cost. Prefer to self-serve? Run the free Scorecard.