AI for Technology & SaaS Companies: Build Better Products, Support Customers Smarter, Scale Efficiently

We architect for performance from day one: caching strategies, async processing, edge deployment, model optimization (quantization, distillation), and load testing. Typical latency: <200ms for most AI features.

We implement privacy-preserving techniques: on-premise/VPC deployment options, data anonymization, zero-retention policies, customer-controlled AI features, SOC 2 compliance, and transparent data handling policies.

Yes. We integrate AI into existing applications through APIs, SDKs, or embedded components. We work with your existing tech stack and don't require full rewrites.

MVP in 6-8 weeks, production-ready in 10-14 weeks for most features. We use agile methodology with weekly demos so you see progress continuously.

We implement guardrails: confidence thresholds, human-in-the-loop for low-confidence cases, monitoring and alerting, easy user feedback, and continuous improvement loops. We also provide rollback capabilities.

We design for scale: auto-scaling infrastructure, caching layers, efficient model serving, edge deployment where appropriate, and monitoring to anticipate capacity needs.

Yes. We can fine-tune models on your data (with proper security controls), build RAG systems using your knowledge base, or train custom models from scratch if needed.

We provide 30 days of post-launch support, plus optional managed services. Most AI features need retraining quarterly or annually, monitoring dashboards, and occasional prompt/threshold tuning.