A fintech company wanted to adopt procurement automation through AI agents but faced uncertainty about data quality, workflow alignment, and system integration feasibility. Leadership needed a structured approach to confirm where AI could add value and how to deploy without risk.
Our Approach: Three Lenses to Assess Before You Start
We applied a simple but rigorous readiness framework:
- Workflow Suitability — Are processes exception-heavy, repetitive, and rules-based enough for AI to add value?
- Data & System Access — Are data feeds and APIs accessible, stable, and clean enough for use?
- Value vs Effort — Is the potential business impact worth the estimated integration complexity?
12-Week Roadmap
- Weeks 1–3 | Discovery & Alignment
Mapped procurement workflows, pain points, and data flows. Identified high-friction/high-value opportunities and aligned stakeholders on goals. - Weeks 4–6 | System & Data Readiness
Evaluated APIs, integrations, and data quality across ERPs and contract systems. Designed initial technical architecture and identified compliance requirements. - Weeks 7–9 | Agent Feasibility & Prioritization
Scored candidate agents on impact and complexity, defined deployment sequence for early wins, and validated sequencing logic with stakeholders. - Weeks 10–12 | Architecture & Implementation Plan
Delivered a ranked agent list, integration blueprint, and governance framework with timelines for deployment.
Results
- Deployment-ready in 12 weeks, avoiding typical 6–12 month delays.
- Identified 3 priority agents (intake, renewals, and spend analysis) with clear ROI.
- Delivered a full implementation plan — integration map, reusable components, and governance guardrails — giving the client confidence to launch without guesswork or rework.
Why It Matters
Instead of experimenting blindly, the client gained a structured runway: clean data, aligned workflows, and a ranked roadmap of agent deployments. The foundation was set for rapid automation, with zero integration surprises and a clear ROI path.