AI is only useful when it ships — and stays shipped.
ByteWave has deployed hundreds of ML and GenAI systems into production at regulated enterprises — not into Notion pages. We stand up the data, the feature store, the model, the evaluation harness, the safety guardrails and the MLOps pipelines. We instrument the business KPI before the first model is trained, because the only model that matters is the one that moves a number on a dashboard.
What we deliver
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01
Enterprise copilots & RAG Custom copilots on Azure OpenAI, AWS Bedrock, Vertex AI, Snowflake Cortex AI, Databricks Mosaic AI. RAG over Snowflake / Databricks / vector DB with hybrid search.
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02
Document intelligence Contract analysis, KYC extraction, claims triage, invoice OCR, IDP. LayoutLM, Donut, multimodal LLMs, human-in-the-loop review.
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03
Demand forecasting & planning Hierarchical forecasting, promo uplift, new-product ramp, ML-on-Snowflake / Databricks, scenario planning, what-if simulation.
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04
Customer churn & lifetime value Survival models, uplift modeling, next-best-offer, propensity scoring. Real-time scoring with feature stores and reverse ETL.
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05
Fraud, AML & anomaly detection Graph neural networks, isolation forests, sequence models, streaming inference. Explainable, regulator-aligned, MLOps-grade.
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06
MLOps & feature platforms MLflow, Tecton, Databricks Feature Store, Snowflake Feature Store, Weights & Biases, Evidently, A/B testing, canary & shadow deploy.
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07
LLMOps & evaluation Prompt management, evaluation harnesses, hallucination guards, guardrails (NeMo, Guardrails AI), cost / latency budgets, observability.
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08
Responsible AI & AI Act compliance Model cards, bias audits, EU AI Act readiness, NIST AI RMF, ISO/IEC 42001 alignment, data lineage, retention, consent.
Engagement model
AI opportunity assessment (4 weeks), data readiness audit, target architecture, pilot sprint, production rollout in waves, MLOps handover and managed model operations. Each engagement is led by a senior applied-AI architect with regulated-industry experience.
Outcomes you can measure
- Sales forecast MAPE reduced 41% with hierarchical ML.
- Customer churn cut 17% with propensity + retention plays.
- Claims processing time cut 65% with document AI + human review.
- Field engineer productivity up 28% with copilot + knowledge RAG.
- Fraud loss rate cut 38% with graph ML + streaming inference.