Natural-language professional search and enrichment console

For

Sales, recruiting and research teams that find and qualify professionals across large profile databases or connected accounts

Solves

Finding the right professionals across several profile databases and connected accounts requires separate subscriptions, manual filters and scattered verification.

Delivers

Reviewed, source-linked candidate list with verified contact details and intent signals

Built in

about 5 weeks of creation time, MVP in 6 days

Investment

$13,000 for the MVP, $44,000 for the full product

Run it

Inside your business, or as part of your offer to clients

Reduce the number of tools and manual steps needed to find and qualify professionals.

1. Accept natural-language descriptions of the person to find.
2. Search permitted large profile databases and connected accounts.
3. Return verified phone numbers, emails and social links with source links.
4. Generate AI insights about each match.
5. Enrich profiles with deeper context beyond basic details.
6. Share research and data in a team workspace.
7. Run specialized alumni searches across universities.
8. Index contacts and interactions from connected email, calendar and social accounts.
9. Extend searches into trusted contacts' networks for warmer introductions.
10. Crawl public web sources in real time for people and companies.
11. Cross-reference details and show source links for identity verification.
12. Upload a CSV and append data points from multiple sources.
13. Score intent signals such as job changes or funding events for urgency and fit.
14. Send personalized messages through connected accounts with paced sending.
15. Connect results to sales, hiring, spreadsheet and collaboration tools.
16. Offer a free tier for exploration and low-volume use.
17. Compare the reviewed result with the recorded baseline and value assumptions.
18. Capture corrections and named-owner approval before consequential use.
19. Export a versioned reviewed, source-linked candidate list with verified contact details and intent signals, source references and unresolved questions.

Everything these tools do, in one app

• Natural language search Allows users to describe the person they want to find in plain language instead of using complex filters.Found in People Search GPT by Redrob, Clado Atlas, Clado and 2 more
• Large profile database Provides access to a vast collection of professional profiles from multiple sources.Found in People Search GPT by Redrob, Clado Atlas, Clado
• Verified contact details Supplies verified phone numbers, emails, and social links for the people found.Found in People Search GPT by Redrob
• AI-powered insights Offers AI-generated insights about matches to help users better understand prospects.Found in People Search GPT by Redrob, Clado Atlas
• Profile enrichment Adds deeper information and context to profiles beyond basic details.Found in Clado Atlas, Lev8
• Team collaboration Enables teams to share research and data within a collaborative workspace.Found in Clado Atlas
• Alumni search Specialized search to find students and graduates across universities.Found in Clado
• Cross-account indexing Indexes contacts and interactions from connected email, calendar, and social accounts.Found in Happenstance
• Friend and group sharing Extends searches into trusted contacts' networks to find warmer introductions.Found in Happenstance
• Live web search Crawls public web sources in real time to find people and companies.Found in Lev8
• Identity verification Cross-references details and provides source links so users can verify information.Found in Lev8
• CSV enrichment Uploads a CSV and appends additional data points from multiple sources.Found in Lev8
• Intent signal monitoring Scores signals like job changes or funding events for urgency and fit.Found in Lev8
• Multi-channel outreach Sends personalized messages through connected accounts with paced sending.Found in Lev8
• Workflow integrations Connects with sales, hiring, spreadsheet, and collaboration tools to keep results in existing workflows.Found in Clado Atlas, Happenstance
• Free tier Offers free access to core features for exploration and low-volume use.Found in Clado Atlas, Clado, Happenstance and 1 more

What goes in, what comes out

The workflow

1. In
   Start with

   Permitted profile sources, connected account data, enrichment rules and outreach constraints

2. 1

   Confirm the buyer's problem and scope

3. 2

   Collect permitted profile sources

4. 3

   Connected account data

5. 4

   Enrichment rules and outreach constraints

6. 5

   Then follow this sequence: 1

7. Out
   Finish with

   Reviewed, source-linked candidate list with verified contact details and intent signals

AI does the heavy lifting, people stay in charge

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final identity verification, outreach approval and data-use decisions remain human. A model suggestion is never a verified fact, professional decision or authorization to act.

What your team sees

Primary screens: Query and source setup, Searchable result library, Profile and evidence view, Data stewardship console. Use a search bar for natural-language queries, a filterable result table with saved searches, and a right-hand panel for profile details, source links, enrichment fields and review state. Let users compare candidates side by side. Display draft, needs review, verified and rejected states. Provide a shared team workspace with comments and export. Make the task-specific outcome a reviewed, source-linked candidate list with verified contact details and intent signals visible beside its evidence, review state and value baseline.

Accounts and administration

Project ownership, source permissions, connected account scopes, saved searches, enrichment fields, outreach pacing, team roles, export logs and a rights record for supplied material. Add organization access boundaries, named reviewers, usage caps, data retention controls and explicit approval for external actions such as outreach.

Integrations and data access

Buyer-owned profile sources, authorized connected accounts and permitted public web sources. Cloud storage, CSV import/export, sales, hiring, spreadsheet and collaboration tools. Start with file exchange and validate destination specifications before promising direct synchronization. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

We build with our own AI software development factory, so most implementations take days to a few weeks of creation time, not months. You see working software at every step, and exact timing depends on availability.

1. 1

   Scoping call

   Day 1

   Thirty minutes on your process, your data and how you want to run it: for your own team, or for your clients. You get a fixed scope and price for the MVP.

2. 2

   MVP

   6 days

   One buyer segment, one recurring use case; first modules: accept natural-language descriptions of the person to find; search permitted large profile databases and connected accounts. Manual review in the loop. Built by our AI software factory.

3. 3

   Paid pilot

   7 days

   Accounts, roles, review states, audit trail and the first integration, hardened for two to three paying pilot customers.

4. 4

   Full product

   3 weeks

   Self-serve onboarding, billing, monitoring and the wider integration set.

5. 5

   Run and improve

   Monthly

   We host, monitor and improve it for a fixed monthly fee, or hand it over to your team. How the retainer works.

Why we start with an MVP

An MVP, or minimum viable product, is the smallest version that your users can actually work with. It is not a cheap version of the full solution. It is a test, built to answer the questions that decide whether the rest is worth building.

1. Pick the riskiest assumption. Here: will sales, recruiting and research teams that find and qualify professionals across large profile databases or connected accounts use it to solve "finding the right professionals across several profile databases and connected accounts requires separate subscriptions, manual filters and scattered verification"?
2. Build only what tests it. One team, one use case, a few core modules. People do the rest by hand for now.
3. Run a paid pilot. Agree quality and outcome thresholds before the pilot using this measure: Qualified candidates per research hour and verified-contact accuracy.
4. Measure, then decide. Track qualified candidates per research hour and verified-contact accuracy; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase. Then expand, change course or stop, with evidence instead of opinions.

MVP scope for this solution. Pilot scope: One permitted profile source and one connected account type; final identity verification, outreach approval and data-use decisions remain human. Implement one approved input format, a bounded representative case set and the first two task modules: accept natural-language descriptions of the person to find; search permitted large profile databases and connected accounts. Support the remaining modules with operator review. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

After the MVP. Once paid pilots prove usefulness, automate repeatable reviewed steps and add one verified source integration. Expand supported inputs and case volume only after new evaluation cases pass. Build reusable customer configurations and recurring value reports around the reviewed, source-linked candidate list with verified contact details and intent signals. Retain the explicit scope boundary: One permitted profile source and one connected account type; final identity verification, outreach approval and data-use decisions remain human.

What the build depends on. Source upload and preview, asynchronous search and enrichment jobs, editable version history, reviewer access and tested export formats. High-fidelity verification requires specialist data QA. Obtain representative authorized cases, baseline measurements, qualified reviewers and a buyer-side decision owner. Specific limitation: One permitted profile source and one connected account type; final identity verification, outreach approval and data-use decisions remain human.

A planning range to start the conversation, not a quote. You pay per phase, so you can stop after the MVP.

Running costs per month

A rough indication of monthly hosting and AI model costs once it is live, not tested. Real costs depend on usage, file sizes and the models chosen.

Your brand, or this one

Run it under your own brand, or start from this concept style.

Selling it to your own clients: the go-to-market playbook

Pricing to test

Test a USD 300-1,500 fixed pilot for one defined search and enrichment package. Offer a monthly production allowance after repeat demand. Quote complex integrations or specialist data sources separately. These are test prices, not market benchmarks. Package the initial sale as one bounded reviewed, source-linked candidate list with verified contact details and intent signals. Recurring fees must specify volume, review depth and integration support. For exchanges, test a disclosed coordination or successful-service fee rather than holding customer funds. Reprice only after measuring real delivery labor; platform-build cost is separate from a commercial pilot fee.

Message to test

Reduce the number of tools and manual steps needed to find and qualify professionals. Demonstrate a concrete reviewed, source-linked candidate list with verified contact details and intent signals using the buyer's approved example and show the baseline, corrections and actual delivery effort.

Where to find buyers

Sales, recruiting and research teams professional communities; specialist consultants serving this buyer; permissioned partner introductions; practical demonstrations at relevant trade or practitioner events.

Lead magnet

A reviewed sample reviewed, source-linked candidate list with verified contact details and intent signals from a small authorized input set, with a transparent calculation of qualified candidates per research hour and verified-contact accuracy and no promised savings.

The first 30 days

1. Week 1: interview five sales, recruiting and research teams that find and qualify professionals across large profile databases or connected accounts and inspect a recent example of finding the right professionals across several profile databases and connected accounts requires separate subscriptions, manual filters and scattered verification.
2. Week 2: prepare a consented or synthetic demonstration of the three task modules.
3. Week 3: seek one bounded paid pilot with agreed baseline and acceptance criteria.
4. Week 4: measure qualified candidates per research hour and verified-contact accuracy, reviewer effort and repeat-purchase interest. This is a demand-validation plan, not a thirty-day full-product delivery promise.

Paid pilot

Agree quality and outcome thresholds before the pilot using this measure: Qualified candidates per research hour and verified-contact accuracy. Continue only if the buyer accepts the actual output, the intended job outcome improves without unacceptable errors, and measured delivery cost fits willingness to pay. Revise or stop if access is unavailable, qualified review cannot be provided, or apparent savings disappear after corrections and support. Use held-out cases when comparing model quality; use a properly reviewed comparison design before making causal claims. Record missing cases and negative results alongside successful outputs.

Success metrics

Qualified candidates per research hour and verified-contact accuracy; accepted-output rate; material error rate; reviewer correction time; actual repeat purchase.

Retention and expansion

Repeat the workflow when the buyer again needs a reviewed, source-linked candidate list with verified contact details and intent signals. Retain permissioned settings and reviewed examples, report realized value honestly, and sell increased volume or adjacent approved workflows only after contribution margin and quality remain acceptable.

Why clients would pick it

A reusable library of approved search patterns, source permissions and review examples, together with reliable delivery for a narrow research niche. Build a permissioned library of representative task cases, reviewer corrections and verified operating constraints for sales, recruiting and research teams that find and qualify professionals across large profile databases or connected accounts. Repeatable delivery and useful integrations matter more than access to a base model.

Alternatives and positioning

People Search GPT by Redrob, Clado Atlas, Clado, Happenstance and Lev8, plus manual searching and spreadsheets. Compare this product with the buyer's present method on qualified candidates per research hour and verified-contact accuracy. Offer a bounded paid workflow instead of claiming broad autonomous expertise. Market uniqueness and competitor coverage are not verified.

Main delivery costs

Search and enrichment attempts, data source access, storage, reviewer hours, client revision rounds and licensed source data. Additional initial validation requires representative authorized sample preparation, buyer interviews, buyer-side evaluation and bounded validation of the reviewed, source-linked candidate list with verified contact details and intent signals. Track cost per accepted output, including correction work, unsuccessful cases and support.

Preserve source attribution, contact accuracy, consent and usage permissions. Named owners approve outreach and data use. One permitted profile source and one connected account type; final identity verification, outreach approval and data-use decisions remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.