Industrial Prospecting & AI-Assisted B2B Intelligence Workflow
Client / Organization: Industrial B2B Operations
Commercial Challenge & Context
Manual prospecting in the industrial equipment and manufacturing sector was painfully slow. Identifying engineering buyers, verifying facility certifications, and compiling company intelligence required up to 45 minutes per company.
Nicholas Anyim's Specific Role & Responsibilities
AI Workflow Architect & Integration Engineer. Built the automated research pipeline, multi-step prompt chaining, and lead scoring interface.
Engineering Approach & Solution Delivered
Developed an automated B2B intelligence pipeline combining company domain discovery, structured web scraping, LLM-driven company profile summarization, and automated contact enrichment into a centralized lead database.
Technical Decisions & Architecture
- Engineered prompt chains with strict JSON schema validation to prevent LLM hallucinations.
- Integrated automated validation rules verifying business emails, domain active status, and corporate officer records.
- Built an administrative review queue allowing sales strategists to inspect and approve enriched leads before any CRM export.
- Protected API credentials and implemented rate-limiting to prevent vendor API throttling.
Technologies Deployed
Verified Technical & Commercial Outcomes
-80%
Research Time
Reduced per-account research from 45 min to under 8 min
High
Data Fidelity
Strict JSON schema parsing and schema validation
100%
Human Oversight
Mandatory review gate prior to CRM outreach

