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Evaluating 30+ AI Vendors to Deploy 10 High-Impact Solutions
Built a standardized vendor evaluation framework for a mid-market investment firm that cut a backlog of 30+ AI vendors down to 10 realized solutions, resulting in 60% time savings on high-ROI workflows.
The Problem
The same mid-market investment firm was being approached by dozens of AI vendors — from new startups to legacy enterprise providers — each promising transformative results. Without a structured evaluation process, the firm had accumulated a backlog of 30+ potential vendor relationships with no objective way to separate noise from value or measure actual ROI.
Our Approach
Standardized the vendor evaluation process with a repeatable framework covering technical capability, integration feasibility, data security requirements, and business-case alignment. Ran structured pilot programs with objective benchmarks for each candidate vendor. Mapped winning solutions to the firm's highest-ROI use cases and managed deployment into production workflows. Also led monthly AI training sessions to drive adoption, with customized programs and hands-on workshops tailored to each team.
The Outcome
Reduced the vendor backlog from 30+ to 10 realized, deployed solutions. Applied vendor platforms to high-value workflows resulting in 60% time savings. Cross-training and upskilling programs increased AI adoption rates across employees and surfaced new enablement opportunities from stakeholder feedback.
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