AI/ML Development Services for Mid‑Market & Enterprise

Reliable predictive models that drive decisions. - Supervised: churn, credit/risk, pricing, demand - Unsupervised: clustering, anomaly detection, topic modeling - Semi‑supervised: extract value from limited labels

CNNs, Transformers, and GNNs for vision, language, audio, and multi‑modal data. Compression and quantization for faster inference on edge and mobile.

Document and conversation intelligence: NER, summarization, intent, entity linking, semantic search, and RAG with offline/online evaluations.

Real‑time detection, classification, OCR, and segmentation for QA, safety monitoring, and remote sensing.

Time‑series, causal impact, and probabilistic models. Precise confidence intervals, backtests, and decision thresholds.

Personalization engines—collaborative, content‑based, and hybrid. Bias checks, offline A/B tests, and online experimentation.

LLM‑powered assistants and workflows. - RAG done right: chunking, retrieval filters, grounding, and guardrails - LLMOps: prompt/version control, evaluation suites, quality and safety gates - Fine‑tuning & adapters: domain specificity without runaway cost

Policy optimization for pricing, inventory, routing, allocation, and control. Simulators and reward shaping for safer training.

CI/CD for ML, feature stores, model registry, canary/blue‑green releases, telemetry, drift and data‑quality alerts, and rollback plans.

Low‑latency inference near sensors. Streaming analytics and offline‑tolerant designs for plants, warehouses, and field devices.

Roadmaps, business cases, governance, and change. We set KPIs and data contracts before any build.

Ship AI safely: role‑based access, privacy by design, audit trails, explainability, PII/PHI handling, and EU AI Act‑aligned documentation where applicable.