Basil Consulting
Basil Consulting builds the decision layer for enterprises, combining AI forecasting, real-time data platforms, and autonomous agents to turn analytics from retrospective reporting into operational advantage. The firm delivers production systems across nine capabilities, including decision intelligence, generative AI agents, and MLOps infrastructure, with engagements priced from $150k to $320k. Each project ends with a measurement harness and named internal owner to ensure value is verifiable after handover.
- Artificial Intelligence
- Data & Analytics
- AI Agents
- Enterprise Software
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Enterprise analytics functions typically produce retrospective reports that arrive too late to influence operational decisions, leaving organizations unable to act on data in real time. Most companies lack the architecture, forecasting accuracy, and automated decisioning needed to convert raw data into a compounding competitive advantage.
Solution
Basil Consulting designs and builds the decision layer for enterprises, combining AI forecasting, real-time data platforms, and autonomous agents that turn analytics from a monthly report into an operating advantage. The firm operates across nine capabilities, including decision intelligence systems, predictive and prescriptive analytics, modern data platform engineering, generative AI agents, MLOps infrastructure, data governance, customer intelligence, process automation, and fractional CDO leadership. Each engagement ends with a production system, a measurement harness, and a named internal owner, ensuring value is measurable after handover. The delivery method runs five phases—diagnose, architect, build, and beyond—with fortnightly production increments and no six-month reveal.
Target Audience
Primary customers are enterprises with existing data estates that need to move from reporting to decisioning, including finance, operations, and commercial teams seeking production-grade AI systems with measurable ROI.
Features
- Decision intelligence systems that close the loop between insight and action with simulation, recommendation, and automated action wired into operations
- Predictive and prescriptive analytics engineered for accuracy under drift, with explainability sufficient to survive audit committee review
- Lakehouse architecture with streaming ingestion and governed semantic layers as the foundation of the analytics estate
- Generative AI and autonomous agents built on proprietary data, with evaluation harnesses to keep them honest in production
- MLOps machinery including feature stores, model registries, and CI/CD for models enabling weekly data science shipping
- Data governance and AI assurance aligned to EU AI Act, GDPR, SOC 2, and sector regulation, designed to accelerate delivery
- Process intelligence and automation using process mining to expose bottlenecks, rework, and leakage before targeted automation
- Data strategy and fractional CDO leadership providing board-level strategy and operating model design