How to Start with Extruct AI

Extruct AI supports company research, market analysis, and intelligence gathering workflows. Instead of building brittle filters, you describe your ideal profile in natural language and then score candidates against your criteria.

On This Page

1. What Makes Extruct Different
2. How the Search Process Works
3. Custom Data Enrichment
4. Finding and Enriching Contacts
5. Adding Companies for Further Research
6. Getting Started Tips

What Makes Extruct Different

Extruct AI is built for targeted, high-context search rather than broad category filtering. You describe exactly what you need, and the system resolves that into specific research constraints.

Examples:

• Plywood companies with their own production facilities in the European Union
• AI startups founded after 2023 by Harvard graduates
• Venture funds in Iberia focused on early-stage startups, with minimum pre-seed checks above $200k and life-science focus

The more detail you provide, the better your match quality.

How the Search Process Works

Step 1: Natural Language Search

Describe your ideal company profile in plain English.

Examples:

• RICS registered property managers in London
• Biotech companies with oncology pipelines and FDA approval
• Series B companies using Kubernetes in production
• Manufacturing companies with ISO 27001 compliance

Extruct generates an initial candidate set and maps your query into actionable dimensions (location, qualification, business context, etc.).

Step 2: Scoring Against Parameters

Each company is scored against your criteria.

• 100%: perfect match
• 0%: no match
• 1-99%: partial match

Lower-fit rows do not consume credits, so cost tracks relevance.

Step 3: Expand Your Search

Use Find More to generate additional candidate batches. In practice, 2-4 iterations usually produce a strong working dataset.

Custom Data Enrichment

After identifying target companies, add custom columns with explicit prompts. Your prompt defines what to research, where to look, and how to interpret results.

Examples of custom columns:

• RICS verification status
• Property types managed
• ESG compliance score
• Recent funding rounds
• Technology stack

You can also pull from Extruct’s built-in column library for common fields.

Finding and Enriching Contacts

AI-Powered People Search

Extruct can find relevant contacts at target companies via role-based prompts.

Example searches:

• VPs of Sales at Series B SaaS companies
• CTOs at AI startups
• Procurement managers at manufacturing companies
• Founders and C-suite at venture-backed companies

Waterfall Contact Enrichment

Extruct enriches contacts via multi-provider waterfall queries.

Benefits:

• Maximum coverage through sequential provider querying
• Higher quality through cross-source validation
• Cost efficiency by paying for successful enrichments
• Current data through live provider updates

Adding Companies for Further Research

You can build research lists from:

• Search results
• CSV import
• HubSpot integration
• Affinity integration

Multiple search runs can be merged into one table for deeper enrichment and analysis.

Getting Started Tips

1. Be specific in your prompt.
2. Avoid overly broad queries.
3. Run multiple iterations before deciding list quality.

If you want help improving your query strategy, reach out to the Extruct team and share your target profile and constraints.