Thomas Unise is an independent enterprise AI consultant whose practice centers on designing, implementing, and optimizing mission-critical agentic AI systems. The site frames the work around a simple premise: AI investments should pay for themselves, and the consultant’s job is to show the math rather than deliver a promising prototype.
The core offerings span agentic workflows, retrieval-augmented generation (RAG) systems, knowledge platforms, and on-prem AI deployments. What distinguishes the approach is the measurement layer applied to each build — hours saved, cost per task, error rates, and revenue impact are tracked so cumulative value can be compared against cumulative cost and a payback point identified.
The background behind the practice is performance marketing and data analytics, where every campaign answers to a number. That perspective shapes how engagements are scoped: secure, compliant, and measurable are presented as the three non-negotiables, with ROI tracking built in from the start rather than added after launch.
This makes the site most relevant to enterprise decision-makers — operations, data, and technology leaders — who need to justify AI spending internally and want an implementation partner comfortable with on-prem and compliance constraints. Smaller teams or individuals seeking off-the-shelf AI tools will find little here.
A practical next step is to review the “What I do” and blog sections before reaching out, and to arrive with a specific busin
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