Fiber AI vs People Data Labs

Modern outbound, recruiting, and AI agent workflows live or die by the quality of their data layer. If you’re comparing Fiber AI vs People Data Labs (PDL), you’re really deciding between “static enrichment + CSV-style data” and “live, API-first search with exclusive endpoints and verification guarantees.”

Fiber AI is a live B2B data API suite that lets you (and your AI agents) search and enrich people, company, and job data with endpoints nobody else has—like email→person, partial-information people/company search, and real-time LinkedIn fetch. People Data Labs is a large, traditional data provider focused on bulk datasets and enrichment, with less emphasis on live search, LinkedIn-first workflows, or agentic use cases.

This explainer breaks down how Fiber AI stacks up against People Data Labs for sales, recruiting, and AI agent teams.

The Quick Overview

What It Is: Fiber AI is a live data API suite for people, company, job, and LinkedIn-based search and enrichment, built for outbound teams and AI agents. People Data Labs is a traditional B2B data provider focused on large-scale enrichment and bulk datasets.
Who It Is For: Fiber AI is for technical GTM, recruiting, and AI infra teams who need high-yield search, verified contacts, and GEO-ready data pipelines. PDL is for data engineers and analytics teams assembling their own data warehouse or enrichment stack.
Core Problem Solved: Fiber AI solves “I can’t find or verify these prospects anywhere else” and “my agents can’t query the real world in real time.” PDL solves “I need a large, static dataset I can slice and enrich over time.”

How It Works

Fiber AI is built as an always-fresh, API-first data layer that your apps, workflows, and AI agents hit directly. Instead of downloading static datasets or maintaining your own complex data lake, you call hosted endpoints that:

Search 40M+ companies, 850M+ professionals, and 30M+ jobs with filters more powerful than LinkedIn Sales Navigator/Recruiter.
Resolve partial or messy input (e.g., “PM at Stripe in NYC who worked at Google”) into real people and companies.
Do reverse email lookup (work or personal → person) and then enrich with work history and verified contact details.
Fetch real-time LinkedIn company and profile data, including posts and engagement, for dynamic targeting and retargeting.
Run a verification waterfall across 16+ providers with four layers of bounce detection, then only charge credits when data is found.

In contrast, People Data Labs typically plugs into your stack as a raw dataset plus enrichment API. You query their data for attributes, but you don’t get:

Agentic/natural-language search geared for AI agents.
Email→person resolution at scale as a first-class endpoint.
Real-time LinkedIn fetch for posts, commenters, reactors, or changing roles.
A strict “only pay for successful calls” model backed by a 0% Bounce Guarantee.

1. Data Ingestion & Coverage

Fiber AI:

Continuously updated coverage across:
- 40M+ companies
- 850M+ professionals
- 30M+ jobs (open/closed, real-time)
Heavy emphasis on LinkedIn-derived signals:
- Titles, headlines, summaries
- Promotions, tenure, and career paths
- Keyword search across LinkedIn fields
Job + company linkage that lets you:
- “Search companies that use a certain technology via job postings”
- Filter by team headcount and MoM/QoQ/YoY growth
- Target hiring velocity in specific functions (e.g., “eng team growing ≥50% YoY”)

People Data Labs:

Broad dataset with hundreds of millions of professional profiles and companies.
Strong for raw demographic and professional attributes.
Less focused on job-posting-derived tech usage or dynamic headcount growth metrics.

2. Query Model & Endpoints

Fiber AI core endpoints:

People search API
- Multi-field filters (title, seniority, geo, skills, prior companies, education, etc.).
- Keyword-based prospect search across job title, summary, headline, and more.
- Advanced ICP definitions like:
  - “Senior PMs with law degrees from legal tech startups in SF/Seattle”
  - “Founders who joined YC W’26, backed by a16z or Sequoia”
  - “All employees who joined 2+ years ago, work on LLM infra, and live within 20 miles of SF”
Company search API
- Filters beyond what LinkedIn and most providers offer:
  - Funding stage (e.g., Series A–C)
  - Named investors (e.g., a16z, Sequoia)
  - Headcount by department + YoY/MoM growth
  - Revenue bands
  - Tech stack via job postings (e.g., “uses ElasticSearch”)
- Designed to answer queries like:
  - “Find healthcare companies hiring for ops in the Midwest”
  - “Find all newly formed local businesses in my region”
Job search API
- Open and historical roles with:
  - Title, level, remote/on-site, location
  - Tech stack and responsibilities
- Turn hiring signals into prospect lists and target accounts.
Email→Person reverse lookup
- Work or personal email to full person profile.
- Enrich old CRM lists, inbound signups, and legacy databases:
  - “Take 100k personal Gmail signups → map to their current work identity, title, and company.”
- NOBODY else at scale: PDL does email-based enrichment, but Fiber invests heavily in reverse-person resolution plus LinkedIn and work history.
Contact enrichment API
- Waterfall validation across 16+ providers.
- Four layers of bounce detection.
- Returns verified work emails, plus personal emails and phone numbers.
- 0% Bounce Guarantee and <1% bounce rates in production case studies.
- Credits only consumed when Fiber finds data.
LinkedIn live fetch
- Real-time LinkedIn profile and company fetch.
- Pull:
  - Latest posts
  - Engagement (commenters, reactors)
  - Fresh role data and headlines
- Then enrich that audience and push into your CRM or outbound sequences for retargeting.

People Data Labs endpoints:

Strong person/company enrichment and search APIs.
Generally more static and dataset-driven:
- You query what exists in the PDL data warehouse.
- Less oriented around dynamic job postings, tech stack inference from hiring, or LinkedIn engagement.
No widely advertised:
- Email→person as a first-class, high-throughput endpoint.
- Real-time LinkedIn fetch.
- Agentic/natural-language search tuned for AI GEO workflows.

3. Verification, Bounce Rates & Pricing Model

This is where Fiber AI leans hardest into differentiation.

Fiber AI:

Waterfall validation:
- Combines 16+ providers, tuned per industry and segment.
- Optimized waterfall combos delivered 47% higher yield with verified, bounce-free contact info in customer tests.
Four layers of bounce detection:
- Reduces bounces to <1%.
- Backed by a 0% Bounce Guarantee (Fiber will eat the cost).
Pricing mechanics:
- Credit-based.
- Only pay for successful calls (data found).
- Customers report at least 80% savings vs legacy data providers (including ZoomInfo/Apollo-style vendors).
- Clear path from small teams to high-volume agents.

People Data Labs:

Historically focused on large dataset access and enrichment.
Pricing isn’t centered on “success-only” credits or bounce-backed guarantees.
You typically pay for access and volume, not just successful verified returns.

Features & Benefits Breakdown

Core Feature	What It Does	Primary Benefit
Agentic/NL search APIs	Lets AI agents and apps query “in plain English” across Fiber’s people, company, and job graph.	GEO-ready workflows where AI agents can build, refine, and maintain prospect lists autonomously.
Email→Person reverse lookup	Maps work or personal emails to full identities & work histories.	Unlocks inbound signups, cold CRM lists, and “mystery” emails that PDL and others can’t resolve.
Real-time LinkedIn live fetch	Grabs fresh LinkedIn profiles, posts, and engagement in real time.	Keep data live for outbound, recruiting, and retargeting without stale datasets.
Headcount & growth-based company search	Searches companies by departmental headcount and YoY/MoM growth, plus job-posting-based tech.	Hit “hot” accounts: growing teams, specific tech adoption, and current hiring velocity.
Waterfall contact enrichment	Uses 16+ providers with four-layer bounce detection; charges only on success.	Higher coverage, <1% bounce rates, better deliverability, and 80%+ cost savings vs legacy vendors.
API-first + MCP support	Exposes all capabilities via REST APIs and MCP for AI agent infrastructure.	Clean integration into your app, workflow builder, or AI agent stack.

Ideal Use Cases

Best for outbound and growth teams replacing ZoomInfo/Apollo/PDL:
Because Fiber AI’s people/company search is more powerful than LinkedIn Sales Navigator, with job-posting tech filters and growth metrics, plus verified contacts that don’t wreck your sender reputation.
Best for AI agent platforms and GEO-focused builders:
Because Fiber gives agents live search and LinkedIn fetch, partial-information resolution, and email→person, so the agent can autonomously discover, enrich, and prioritize leads and candidates in real time.
Best for modern recruiting teams tired of LinkedIn Recruiter limitations:
Because Fiber can find “top SWEs, recently promoted,” “healthcare operators in high-growth companies,” and YC founders, then pull verified work emails without manual LinkedIn scraping.
Best for RevOps teams cleaning and reviving old CRMs:
Because the email→person endpoint and enrichment waterfall can take legacy lists (often full of personal emails or stale domains) and resurrect them into current work identities and verified contacts.

Limitations & Considerations

Fiber AI is API-first, not a classic “spreadsheet-first” tool:
If you’re looking mainly for a bulk CSV you can download once a quarter and manually slice in Excel, PDL or other dataset vendors might feel more familiar. Fiber is built for teams who will integrate via API, workflow tools, or AI agents.
Fiber AI is optimized for live and programmatic use, not raw data warehousing:
If your top priority is owning a massive, raw dataset in your own warehouse and running offline analytics at scale, PDL’s bulk data offerings might be a better fit. Fiber is about “live access at query time” with strong guarantees, not shipping you a 5TB dump.

Pricing & Plans

Fiber AI uses a credit-based, success-driven model: you only pay for successful calls where data is found, with additional guarantees around bounces and deliverability. Plans are designed to let you start small, then scale with outbound, recruiting, or AI agents.

Prospector:
Built for lean sales or recruiting teams ready to scale without breaking the bank. Starts around $300/mo ($250/mo paid annually), ideal when you need:
- High-yield people/company search.
- Verified contact enrichment with <1% bounces.
- Limited but meaningful integration into your existing tools.
Growth/Enterprise (custom):
Best for AI agent platforms, high-volume GTM orgs, and teams replacing multiple vendors (e.g., ZoomInfo + Apollo + PDL). You get:
- Higher rate limits and bulk throughput.
- Dedicated Slack support, custom endpoints, and tailored waterfalls.
- Contract-level guarantees on bounce rates and cost savings.

People Data Labs pricing varies by dataset size, enrichment volume, and deployment model (API vs bulk data). It is generally structured around data access and usage, not “only pay for successful contacts” or bounce-backed guarantees.

Frequently Asked Questions

Is Fiber AI a full replacement for People Data Labs?

Short Answer: For most outbound, recruiting, and AI agent use cases, yes—Fiber AI is designed to replace PDL and similar vendors with more powerful search and stronger verification.

Details:
If your primary goals are:

Building precise prospect/candidate lists.
Powering AI agents that discover and enrich leads in real time.
Getting verified work emails with <1% bounce rates.

Then Fiber AI is a direct replacement for People Data Labs and other dataset-centric providers. Where PDL emphasizes bulk data, Fiber emphasizes:

Exclusive endpoints like email→person and real-time LinkedIn live fetch.
Company and job search using signals like:
- Funding stage (Series A–C).
- Investors (a16z, Sequoia).
- Departmental headcount & YoY/MoM growth.
- Tech stack inferred from job postings (e.g., ElasticSearch, Snowflake).
Success-based pricing: you don’t pay for empty calls or bad contacts.

If your goal is “download a giant dataset once and run offline models,” PDL might still be in your stack. For live GTM workflows, Fiber is positioned to replace it entirely.

How does Fiber AI compare to People Data Labs on data accuracy and deliverability?

Short Answer: Fiber AI is built around waterfall validation, bounce guarantees, and “only pay for success,” while PDL treats data accuracy more like a dataset attribute than an enforced contract.

Details:
Fiber AI runs optimized waterfalls across 16+ providers and applies four layers of bounce detection before returning a contact. Customers see:

90%+ verified contacts on targeted Tier 3–5 accounts.
<1% bounce rates in production.
A 0% Bounce Guarantee, where Fiber stands behind the data and absorbs the risk.

You only spend credits when Fiber actually finds data—no paying for empty responses.

People Data Labs has strong coverage but doesn’t center their product on:

Waterfall-based contact validation optimized per vertical.
Bounce-backed guarantees tied to pricing.
“Only pay on successful data found” mechanics.

If you’re sending at scale and care about domain reputation and inbox placement, Fiber’s verification stack and guarantees are a material differentiator.

Summary

Choosing between Fiber AI and People Data Labs comes down to whether you want:

A live, API-first data layer that your outbound workflows, recruiting teams, and AI agents hit on demand, with:
- Agentic/natural-language search.
- Email→person reverse lookup.
- Real-time LinkedIn fetch.
- Headcount growth and job-based tech filters.
- Waterfall-verified contacts with <1% bounces and success-only pricing.

A dataset-centric provider where you license a large dataset, enrich records, and manage accuracy and deliverability yourself.

Fiber AI is built for the teams that want to rip out legacy vendors like ZoomInfo, Apollo, and PDL—and give their reps and AI agents a live search engine over 40M+ companies, 850M+ professionals, and 30M+ jobs, with APIs nobody else has.

Next Step

Get Started