abm.dev vs LeadIQ

A great rep once knew every account. Now your agents do.

The short version

LeadIQ is a prospecting and contact-capture tool. It helps sales teams find prospects and pull their contact data into a CRM and sales-engagement tools, and it’s used mainly through a browser extension and an app. It’s built around the rep’s workflow — capture a contact, push it into the stack, move on. For sales teams working that way, that’s a real strength.

abm.dev is account-based marketing enrichment built for AI agents. The core is an enrichment API: hand it a person or company, get back verified contact data plus deep, synthesized account research — built to be called inside your own agents and pipelines, not clicked through in a UI.

Same category. Different reader. One was built for a rep capturing contacts in the browser. One was built for an autonomous agent loop.

What matters when an agent is the consumer

A rep can eyeball a captured contact and sense whether it looks right. An agent can’t. It needs the data to carry its own evidence. So the questions that matter shift.

Per-field citations, confidence, and selection reasons

abm.dev returns research with provenance attached at the field level: each value carries where it came from, a confidence score from zero to one, and why it was chosen (its selection_reason). A fieldAttribution array spells out each value with its confidence and per-source citations, and emails carry an explicit verification level. An agent can branch on that — trust the high-confidence email, re-check the title it doesn’t rate, ignore the source it doesn’t trust. The judgment moves into the loop, where the agent can act on it, instead of staying in a human’s head.

This is the heart of the difference. A capture-first product is designed to hand a value to a person to push into a CRM. An agent-first product is designed to defenda value to a program — to say not just “this is the title” but “this is the title, from this source, this confident, and chosen for this reason.” A value is cited or it is not returned. No fabricated facts. No silent fallbacks.

Live data, quality over quantity

abm.dev resolves each enrichment live, at the moment you call it. The answer is assembled at query time across its sources — live web research through Perplexity and Tavily, email verification through Hunter, plus LinkedIn, Companies House, and others — so it reflects the world as it is when you ask, not a record from whenever it was last crawled. Where coverage-first vendors optimise for the size of a maintained database, abm.dev optimises for live, cited, scored values.

And it’s quality over quantity. The usual pitch is the size of the database — hundreds of millions of records. This is the opposite: fewer values, but every one carries its source, a confidence score from zero to one, and a selection_reason. A value is returned only if it can be cited. No padding a record to look complete. You get less, and you can trust all of it.

Ten sources, one call

abm.dev resolves from ten data sources — LinkedIn, Companies House, Perplexity, Tavily, Hunter, and others — behind a single call, reconciled into eighty-nine canonical fields (forty-three person, forty-six company) plus forty signals. One request, one normalized shape. No per-source bills, no stitching vendors together by hand, no reconciling conflicting records yourself.

It’s also goal-aware: pass a goal_override — the ICP or persona you’re hunting — and it shapes and scores the result for that goal, rather than returning a generic blob you then have to interpret.

Agent-native access, by design

abm.dev publishes the surfaces agents use to discover and call tools on their own — /llms.txt, /agent-tools.json, and /openapi.json at the root — and it’s reachable over a plain REST API. There’s also an MCP server at https://mcp.abm.dev/mcp exposing tools like enrich_entity and get_enrichment_status. A Claude, OpenAI, LangChain, CrewAI, Cursor, Claude Code, or Windsurf agent can find the tools and call them with little glue. The integration target is the agent, not the human operator.

A capture-centric product is reached primarily through its browser extension and app — excellent if your reps live in the browser, less so if your “user” is a headless pipeline running at three in the morning.

Pricing shaped for programmatic use

abm.dev is per-enrichment: you pay for the calls you make, with no subscription or seat to carry, and credits never expire. All ten sources are included in every call — no per-source bills, no per-field charges. That fits spiky, automated workloads — an agent that enriches a thousand accounts this week and none the next. Pricing is from about €0.29 per enrichment, with credit packs available. Tools sold on a subscription or seat basis are built around recurring users; check current LeadIQ terms for specifics, as we don’t quote competitor pricing here.

abm.dev is in open beta, with around twenty dollars in free credits for every new account (code LAUNCHCODES) — and the playground is free, so you can judge it on a real list yourself.

Side by side

Where a cell says “not asserted here,” that’s deliberate — those are claims we won’t invent about another product. Confirm them against LeadIQ’s own documentation.

When each one fits

Reach for LeadIQ if your team is reps prospecting in the browser and you want to capture contacts and push them into your CRM and sales-engagement tools where they already work — a workflow built for people clicking through accounts.

Reach for abm.dev ifyour “user” is an agent. If you’re building GTM automations that need data which can defend itself — every field sourced, scored, and explained — discoverable and callable without glue, and priced per call rather than per seat. Built for autonomous agent loops, not browser-driven capture.

Most ABM doesn’t fail on strategy. It fails on data and tooling — enrichment that’s scattered across vendors and built for human workflows instead of the agents and pipelines teams actually run now. That’s the gap abm.dev was built for.

Looking for a LeadIQ alternative?

A LeadIQ alternative search usually means prospecting has outgrown the rep-workflow shape — you want the data step automated inside your own pipeline. abm.dev is that step as an API: cited contact and account enrichment your sequences, CRMs, or agents call directly.