We build and operate multi-tenant, planet-scale AI applications with reliability and governance baked in.

• Tenant isolation, rate-limiting, quotas, and usage metering
• Horizontal scale, autoscaling pipelines, and cost-aware orchestration
• Security, compliance, observability, and lineage across data + models
• Feature stores, vector search, and high-throughput model serving
• Enterprise SLAs with blue/green and canary rollouts

Large-scale cloud AI that natively speaks to edge AI hardware. We engineer bidirectional control and data planes so the cloud and the edge continuously inform each other.

• Streaming inference, telemetry, and feedback loops
• Bidirectional sync for models, configs, and policies
• Low-latency messaging with offline-first buffering
• Digital twin dashboards with remote actions and A/B deployments
• Security from cloud to device: signing, attestation, and RBAC

Power‑efficient AI entirely at the edge — even completely offline. We design for real hardware constraints without sacrificing performance.

• Software deployment, hooks, and embedded integration
• Sensor pipelines and on‑device pre-/post‑processing
• Model optimization: quantization, pruning, compilation
• Power-/thermal-aware scheduling; memory-constrained runtimes
• Offline operation with local rules, safety fallbacks, and OTA when available.