The Brief
A client came to us with a specific problem. They were building a UK community portal for drone professionals in the construction, surveying, engineering, and infrastructure sectors. The portal needed members — specifically, professionals with UAV expertise at major organisations who could bring authority, experience, and credibility to the community.
The brief was straightforward but ambitious: find the right people, understand who they are and why they matter, and deliver something the client could act on immediately. Not a list of Google hits. Not a CSV of names scraped from a directory. A structured, categorised, outreach-ready contact database with enough context to make every conversation count.
The client had no time for a multi-week research project. They needed intelligence, fast. We said we could deliver in under 2 hours — and we did.
"Find me the people who matter in UK construction drones — and tell me why they matter."
What We Did
We deployed a three-agent AI team working in parallel, each handling a distinct part of the intelligence pipeline. The work happened simultaneously, not sequentially — that's how we hit the speed target.
Parallel Execution, Not Sequential Discovery
Traditional research flows one step at a time: identify sources → scrape data → clean it → analyse → format. That's fine if you have a week. If you have two hours, parallel is the only option.
Our coordinator agent (Bee) broke the brief into three independent workstreams:
- Directory scraping and contact discovery — handled by our research agent (Gav), systematically mapping six structured data sources including the Drone Survey Directory, ARPAS-UK, Drone Safe Register, The Survey Association, RICS Find a Surveyor, and CICES.
- Taxonomy and framework design — handled by our framework designer (Mel), building a 6-dimension categorisation model tailored to the client's community structure.
- Quality verification and gap analysis — handled by Bee, cross-referencing discoveries against the framework and flagging gaps for Phase 2.
Because each stream was independent, they ran simultaneously. Scraping didn't wait for the taxonomy. The taxonomy didn't wait for a completed dataset. The coordinator stitched them together at the end.
The Taxonomy: Six Dimensions of Fit
Every contact was scored across six dimensions, producing a structured assessment of their relevance to the client's community:
- Sector — Which industry sector they operate in (construction, surveying, engineering, infrastructure, or multi-sector)
- Role Type — Their position in the drone ecosystem (in-house UAV lead, drone service provider, engineering consultant, survey contractor, trainer, regulator, technology vendor, academic, owner, project manager)
- Organisation Type — The size and nature of their employer (solo operator, SME, large contractor, consultancy, public body, trade association, academic institution)
- Region — Geographic coverage across 12 UK regions
- Community Fit — A HIGH/MEDIUM/LOW assessment of how well they align with the portal's community-driven mission
- Service Tags — Specific capabilities (LiDAR, photogrammetry, thermography, BVLOS, surveying, inspection, training, and more)
This framework wasn't generic. It was designed specifically for the client's community model. Each dimension answered a practical question: who are they, what do they do, where are they based, and how well do they fit the community's purpose?
What Was Produced
The client received five deliverables, all produced within the two-hour window:
1. Master Contact Database
A structured spreadsheet with 46 named individuals across five tiers — from senior infrastructure drone leads at organisations like National Highways and Network Rail, through to independent surveying companies operating in every UK region. Each record included name, job title, company, website, LinkedIn URL, region, and classification across all six taxonomy dimensions.
2. Company Directory
70 UK drone companies with full contact details — websites, regions, phone numbers where publicly listed — systematically scraped from structured directory sources. Covering the full spectrum from national infrastructure organisations to regional independent operators.
3. Categorisation Framework
The 6-dimension taxonomy document, designed to be reusable. As the client adds more contacts in Phase 2, they can apply the same classification system — no need to redesign the framework each time the database grows.
4. Outreach Playbook
Five persona-specific message templates — each tailored to a different type of community member. In-house UAV leads get a different message than independent surveyors. Engineering consultants get a different message than technology vendors. Every template includes the core value proposition, tone guidance, and suggested channel (email vs LinkedIn).
5. Data Schema & Deduplication Rules
A complete data dictionary documenting every column in the contact database, plus a deduplication protocol for merging records when new data sources are added. Phase 2 can scale without breaking what Phase 1 built.
"Here's what we produced in under 2 hours: 46 named individuals, 70 companies, a 6-dimension taxonomy, and a playbook you can use today."
Methodology
The Data Pipeline
Six structured data sources were systematically mapped and explored:
- Drone Survey Directory — A verified UK drone services directory with company listings, regions, and service categories
- ARPAS-UK — The UK's drone trade association directory, providing high-trust, vetted contacts
- Drone Safe Register — CAA-approved drone operators, with insurance verification and structured service tags
- The Survey Association (TSA) — Professional surveying trade body directory
- RICS Find a Surveyor — Chartered surveying professionals with structured location and specialism data
- CICES — Chartered Institution of Civil Engineering Surveyors directory
Each source provided a different lens on the market. Trade associations gave quality-filtered contacts. Structured directories gave consistent, comparable data. Professional bodies added authority and trust signals. Combined, they produced coverage that no single source could deliver.