Use-case discovery, build-vs-buy analysis, ROI modeling, AI readiness audits, and prioritized roadmaps.
Applications built around large language models (Claude, GPT, open-source), retrieval-augmented generation (RAG), and fine-tuning where it makes sense.
Workflow automation across tools like n8n, Make, and Zapier — combined with custom code where the off-the-shelf nodes run out.
Task-specific and multi-agent systems that take action — across email, calendars, CRMs, and internal tools.
Predictive models, classification, recommendation engines, and computer vision, with proper evaluation and MLOps.
Conversational analytics, natural-language-to-SQL interfaces, executive dashboards, and the data pipelines underneath.
Map your processes, data sources, and the metrics that matter.
Identify two to four high-leverage opportunities with clear ROI math.
Build a working pilot in 4–6 weeks against a measurable benchmark.
Productionize, integrate, monitor, and hand off to your team.










