Agentic RFP System for Hennick & Co.
Overview
I designed and demoed an agentic RFP research and application system for Hennick & Co., showing how AI-assisted retrieval, evaluation, drafting, and browser-based workflows could compress a traditionally manual process into a far more scalable operating model.
Client
Hennick & Company is a prominent Toronto-based private investment firm and family office that invests permanent capital into growth-oriented professional services businesses, operating companies, and high-quality real estate.
Challenge
Challenge
RFP discovery and application is slow, repetitive, and mentally draining work for teams that need to find opportunities, research them, evaluate fit, and then complete the application process. Hennick & Co. wanted to simplify that process for partner and child companies by exploring whether an agentic AI system with browser capabilities could handle the heavy lifting while preserving human oversight where needed.
Solution
Solution
I built a Claude-based agentic AI demo system on top of Python, browser automation, orchestration tooling, and cloud data storage. The system was designed to retrieve RFP opportunities, research and record findings, judge fit against a rubric, store structured data, sign up to RFP portals, assist with proposal drafting, and support application submission. Human-in-the-loop checkpoints were preserved for sensitive or blocked steps such as CAPTCHA scenarios and final application review.
Areas of Impact
Areas of Impact
This project demonstrated how a fragmented RFP workflow could be transformed into a coordinated agentic system with retrieval, judgment, memory, and execution layers working together. Instead of treating opportunity search and application as isolated manual tasks, my demo reframed the process as an end-to-end operating system for business development teams.
- Reduced the amount of repetitive manual work required to find and evaluate RFP opportunities
- Showed how rubric-based scoring can improve consistency before teams invest time in a proposal
- Proved that browser-capable agents can move beyond research into real operational workflows
- Created a concrete starting point for a larger production engagement spanning me, 247 Labs, and Hennick & Co.
Results
A functional end-to-end agentic RFP system demo was designed and built within a compressed delivery window.
The demo helped support the start of a larger long-term development opportunity between 247 Labs and Hennick & Co.
Demo performance suggested a major reduction in manual effort across retrieval, evaluation, drafting, and application workflows.
David Hennick
Managing Partner
Hennick & Co.“Wesam architected and delivered a fully functional agentic RFP system in an extraordinarily tight timeline. The demo was polished, technically impressive, and directly contributed to closing a significant contract. His ability to design, build, and present complex AI systems quickly is genuinely rare.”
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