Natural-Language Search

Search the way you already think

Traditional people search tools force you to translate intent into filters. Pick a job title from a dropdown. Add a location. Stack boolean operators. Hope the syntax matches what the database expects. By the time you have a query that runs, you have spent more energy on the tool than on the actual question — and you still might have missed the phrasing that would surface the best matches.

Ploid works differently. You describe who you want in plain English — the same way you would brief a colleague. “Series B fintech CTOs in New York who previously worked at a top-10 bank.” “Senior backend engineers in Stockholm who contribute to open-source Rust projects.” “Marketing leaders at mid-market SaaS companies hiring for RevOps.” Ploid interprets the intent, resolves the criteria, and returns structured results without asking you to learn a query language first.

No filters, no boolean, no guesswork

Legacy databases were built for power users who live inside filter panels. That model breaks the moment your criteria span multiple dimensions — career history, company stage, hiring signals, geography, tech stack, and seniority all at once. Boolean strings become unreadable. Filter UIs become endless. And every platform implements the same concepts differently, so the muscle memory you built in one tool does not transfer.

Natural-language search removes that friction entirely. You do not configure fields. You do not maintain saved filter sets. You state the outcome you need and Ploid maps it to the underlying graph — titles, employers, locations, timelines, and signals — then ranks matches across hundreds of sources. When your ask changes, you rewrite one sentence instead of rebuilding a filter tree.

From question to shortlist in one step

The value is not just faster typing. It is faster iteration. Sales teams can refine an ICP in real time during a pipeline review. Recruiters can pivot from one req to the next without opening a new saved search. Founders can pull a prospect list between meetings with a single prompt. Each query returns enriched profiles — verified contact channels, company context, and professional history — ready to export, push to a CRM, or hand to an agent.

Because Ploid draws from over 800 sources and continuously resolves identities across them, natural-language search is not limited to the coverage ceiling of any single vendor. If someone exists professionally on the public internet, Ploid can usually find them — and explain why they matched your ask.

Structured intent, not a black box

Plain English in does not mean opaque results out. Ploid breaks each query into structured intent — role, seniority, company type, geography, timeline, and the other dimensions that define a good match — so you can see how your words were interpreted and adjust when needed. You get the speed of conversation with the precision of a structured search, without choosing between them.

That transparency matters for teams that share searches, document sourcing decisions, or wire Ploid into automated workflows. The query stays human-readable. The output stays schema-validated. Everyone works from the same understanding of who you are trying to reach and why.

Built for every team that searches for people

Natural-language search is the front door to everything else Ploid does — agent fan-out, enrichment, list building, and API access all start with a clear ask. Whether you are in sales, recruiting, marketing, research, or building your own agent on top of Ploid, you should not need a training manual to run your first search. Describe who you want. Get matches back. Move on to the work that actually requires you.