# Exa review (2026): how well its AI agent builds lead lists

By [Florian Martens](https://pipe0.com/authors/florian-martens) · Published Oct 15, 2026

Source: https://pipe0.com/reviews/exa
Scoring method: https://pipe0.com/reviews#methodology
Disclosure: pipe0 buys from Exa and offers its Agent as a list-building search. The scores come from our own benchmark, not from that relationship.

> Exa is a capable general-purpose list builder: describe a list in plain language and its agent searches a large web index for a few hundred accurate rows. It is usually the weaker choice when a filter-based search fits the list, or when the full list is public on one page and can be scraped. Its niche is narrow: lists no filter can describe.

**What we reviewed:** Exa is a search engine built for AI: web search, page contents, answers, research agents and Websets. We reviewed it for one job: building prospect lists for sales and marketing teams from a plain language prompt.

Tested for:

- Local business lists with the Agent API (ultra and medium effort)
- Local businesses through search's places results
- Online brands and trade-show exhibitors, scored against ground truth

Not scored here:

- Web search and contents for RAG and AI apps
- Websets, Exa's list product, which has its own paid plan

**Verdict: 3.9/5.** The best prompt-based list builder we tested: a few hundred accurate rows in minutes, ahead of Parallel every time. When a database filter can describe the list, the filter wins.

| Criterion | Score | Why |
| --- | --- | --- |
| Ease of use | 4.0/5 | A prompt and an output schema in, a structured list out. Runs are asynchronous and take two to six minutes, and search's 10-place cap isn't in the docs. |
| Data quality | 3.5/5 | Rows were mostly precise, 96% on exhibitors, but lists were short (146 to 341 local businesses) and phone coverage swung from 97% to 8%. |
| Pricing value | 3.5/5 | A medium run is $0.10 flat. Ultra is metered and cost us about $1.10 per run, so short lists landed at $3 to $8 per 1,000 rows. |
| API and agent access | 4.5/5 | A hosted MCP server with an agent tool, Python and JavaScript SDKs, spend and time caps per run, and up to 50 runs at once. |
| **Overall** (mean) | **3.9/5** | |

**Best for:**

- A few hundred accurate rows from a prose brief no filter can express
- Lists published on the web, like exhibitors or members, when a sample is enough
- Agents that need list building behind one tool call

**Skip it if:**

- You need thousands of local businesses per city
- You need every entry of a directory, not a sample
- A database filter can describe your list (industry, size, tech stack)
- Your workflow can't wait two to six minutes for a result

**Price:** from Free pay as you go, with $10 in free credit each month. Free plan available.

## Exa at a glance

- **Agent API:** Asynchronous runs from a prompt and an output schema; effort from minimal to ultra ([source](https://exa.ai/docs/reference/agent))
- **Run limits:** Budget $1 to $100 per run; ultra time limit 5 minutes to 3 hours ([source](https://exa.ai/docs/reference/agent))
- **Places:** Local business profiles with address, hours and reviews, served inside search; 10 per call in our tests ([source](https://exa.ai/docs/search/data/sports-weather-places))
- **Rate limits:** Search 10 requests per second; Agent 50 active runs ([source](https://exa.ai/docs/reference/rate-limits))
- **MCP server:** Hosted at mcp.exa.ai/mcp, with search, fetch and agent tools ([source](https://exa.ai/docs/get-started/exa-mcp))
- **SDKs:** Python and JavaScript ([source](https://exa.ai/docs/get-started/exa-mcp))

## What is Exa? [#what-is-exa]

Exa is a search engine built for AI applications. Its API searches the
web, returns page contents, answers questions, and runs research agents.
For sales and marketing teams the relevant part is the Agent API: describe
a list in plain language, define the columns, and it searches, checks and
returns structured rows.

## Can Exa build lead lists? [#can-exa-build-lead-lists]

Yes, lists of a few hundred rows. An Agent run returned 146 to 341 local
businesses per city in our tests, and the rows were accurate. It beat
Parallel's research tasks on every list. Purpose-built data beat it on
volume: DataForSEO's business listings returned two to six times as many
local businesses, in seconds.

Unique rows returned per scenario (pipe0 benchmark, October 2026).

| Product | NYC barbershops | DFW HVAC | Chicago venues | Miami property managers |
| --- | --- | --- | --- | --- |
| DataForSEO Business Listings | 3,959 | 2,147 | 826 | 1,180 |
| Exa Agent, ultra | 1,932 | 341 | 146 | 170 |
| Exa Agent, medium | 217 | 156 | 81 | 100 |
| Parallel Task, pro | 125 | 17 | 82 | 23 |
| Parallel Entity Search | 81 | 150 | 85 | 158 |
| Crustdata | 26 | 280 | 41 | 450 |
| Amplemarket | 26 | – | 100 | 500 |

A run can return far more when the list already exists in one public
source. Asked for New York City barbershops, Exa found the state licence
registry and returned 1,932 rows, 1,715 of them licensed shops. Registry
rows carry legal entity names ("CUTTING POINT CORP") and rarely a phone
number: 8% had one, against 80% in DataForSEO's list.

NYC barbershops against New York State's licence list of 1,952 shops.

| Product | Rows | Matching a licensed shop | Note |
| --- | --- | --- | --- |
| DataForSEO Business Listings | 3,959 | 1,459 | 80% with a phone, all inside NYC ZIP codes |
| Exa Agent, ultra | 1,932 | 1,715 | copied the licence registry; 8% with a phone |
| Exa Agent, medium | 217 | – | all inside NYC, 68% with a phone |
| Parallel Task, pro | 125 | – |  |
| Parallel Entity Search | 81 | – | companies, no addresses |
| Parallel Task, ultra | 62 | – | 55% inside NYC |
| Amplemarket | 26 | – | about 18 real |
| Crustdata | 26 | – | about 8 real |

## How long does an Exa Agent run take, and what does it cost? [#how-long-does-an-exa-agent-run-take-and-what-does-it-cost]

An ultra run takes three to six minutes and costs about $1 to $1.50; a
medium run takes about two minutes for a flat $0.10. Both are slower than
a database query and faster than Parallel's research tasks, which took
eight to fourteen minutes. Ultra's time limit can't be set below five
minutes, so it doesn't suit a step that must answer quickly.

Time per run, from the vendor's own timestamps.

| Product | Time per run |
| --- | --- |
| DataForSEO Business Listings | 2–15 s |
| Parallel Entity Search | 2–5 s |
| Exa Agent, medium | 1.8–2.2 min |
| Exa Agent, ultra | 2.9–5.6 min |
| Parallel FindAll, base | 6.3 min |
| Parallel Task, pro | 7.9–10.3 min |
| Parallel Task, ultra | 11.1–13.8 min |

Because you pay per run, the cost per row depends on how many rows the run
finds: $0.46 to $1.23 per 1,000 rows for medium and $0.76 to $7.53 for
ultra, against $0.37 for DataForSEO.

What pipe0 paid per 1,000 rows, before margin.

| Product | USD per 1,000 rows |
| --- | --- |
| DataForSEO Business Listings | $0.37–0.38 |
| Parallel Entity Search | $0.051–0.062 |
| Exa Agent, medium | $0.46–1.23 |
| Exa Agent, ultra | $0.76–7.53 |
| Parallel FindAll, base | $48 |
| Parallel Task, pro | $0.80–5.88 |
| Parallel Task, ultra | $1.50–4.84 |

## When does a database filter beat Exa? [#when-does-a-database-filter-beat-exa]

Whenever a filter can describe the list. Online-only brands look like
Exa's territory, since they have no storefront to find on a map. But a
company database with a technology filter found three times as many
verified Shopify brands in seconds, and already held 25 of the 26 Exa
found.

US sustainable apparel brands with their own Shopify store. Verified means the domain serves a live Shopify store.

| Search | Rows | Verified Shopify brands | Time | Cost |
| --- | --- | --- | --- | --- |
| Crustdata, Shopify technology filter | 91 | 77 | seconds | 13.7 credits |
| Amplemarket, first page | 50 | 35 | seconds | 2 credits |
| Exa Agent, ultra | 28 | 26 | 165 s | about 65 credits |

Crustdata already held 25 of the 26 brands Exa verified.

The same holds for local businesses with a clear category. Use Exa for
what a filter can't express, then check whether the database had it first.

## Can Exa get every exhibitor or member from a public list? [#can-exa-get-every-exhibitor-or-member-from-a-public-list]

No. It returns an accurate sample of a few hundred, not the whole list. On
a trade show whose 3,194 exhibitors are public on one page, Exa returned
212, and 96% of them were real. A research agent that can read the
directory page directly returned the full list, but only when it found
that page; a typical run returned fewer rows than Exa.

Exhibitors at Natural Products Expo West 2026, against the official list of 3,194, which is public on one directory page.

| Search | Exhibitors found | Share of official list | Time and cost |
| --- | --- | --- | --- |
| Exa Agent, ultra | 212 | 6.6% | about 4 min · about 63 credits · 96% precise |
| Research agent, typical run | about 45 | 1.4% | 1 to 3 min · a few credits |
| Research agent, reached the directory page | full list | 100.0% | about 3 min · 8 credits · 1 run in 9 |

So Exa is the dependable choice when a few hundred correct rows are
enough. When you need every entry, point a scraper or a list-reading agent
at the directory page. We haven't yet tested lists that no single page
holds, such as companies mentioned across many news articles.

## Can Exa's search return local businesses? [#can-exas-search-return-local-businesses]

Yes, 10 at a time. Exa's search returns places with address, phone,
rating and opening hours, and they were precise: 591 of 602 NYC
barbershops were inside the city. Each call returns at most 10 places, so
a city-wide list means splitting the city into ZIP codes yourself. Across
178 NYC ZIP codes that gave 602 unique barbershops in 20 seconds for
$1.25, about 15% of what DataForSEO returned.

## Exa and pipe0 [#exa-and-pipe0]

pipe0 offers Exa's ultra agent as a list-building search, with a $5
spending cap and a 10-minute limit per run, billed from Exa's own reported
cost. Its agent sends local businesses to DataForSEO and filterable
companies to the company databases, and uses Exa for briefs no filter can
express.

## Exa, DataForSEO or Parallel: which should you use? [#exa-dataforseo-or-parallel-which-should-you-use]

Use DataForSEO for local businesses by category, a company database for
anything a filter can describe, and Parallel for researching rows you
already have. Use Exa when the list needs a prose brief and a few hundred
accurate rows are enough.

Which tool to use for which list-building job, from the benchmark.

| Job | DataForSEO | Exa | Parallel | Company databases |
| --- | --- | --- | --- | --- |
| Local businesses by category (e.g. barbershops in new york city) | Best pick: 826 to 3,959 rows per city in seconds | Works: 146 to 341 rows in 3 to 6 minutes | Weak: 17 to 200 rows in 8 to 14 minutes | Weak: 26 barbershops, most of them noise |
| Phone, hours and rating per location (e.g. hvac contractors to call) | Best pick: 80 to 96% of rows with a phone | Mixed: 97% with a phone in Dallas, 8% in NYC | Weak: Entity Search returns no phone | Not built for it: No phone per location |
| Companies by firmographics or tech stack (e.g. us apparel brands on shopify) | Not built for it: Only businesses with a map listing | Weak: 26 brands, 25 already in Crustdata | Not tested: Entity Search wasn't run on this | Best pick: 77 verified Shopify brands in seconds |
| Lists published on the web (e.g. exhibitors at a trade show) | Not built for it: No event or membership data | Works: A few hundred accurate rows per run, never the full list | Not tested: FindAll fits the shape; not run | Not built for it: No exhibited-at filter |
| One researched answer per row (e.g. the imprint page of a small company) | Not built for it: Not a web research tool | Not tested: Not benchmarked for this | Best pick: Task base solved 5 of 5, in 22 to 63 s | Not built for it: Not a web research tool |

## Exa pros and cons

### Pros

- **Beat Parallel on every list.** On four local lists, Exa's ultra agent returned 146 to 1,932 rows in three to six minutes. Parallel's tasks returned 17 to 200 in eight to fourteen.
- **Accurate rows from a prompt.** Rows were real and on target: 96% of the trade-show exhibitors it returned were on the official list, and every NYC row from a medium run was inside the city.
- **Built for agents.** A hosted MCP server, budget and time caps per run, and a structured output schema make it a safe tool to hand an agent.
- **Cheap fixed runs.** Medium effort costs $0.10 a run and returned 81 to 217 local businesses in about two minutes, every NYC row inside the city.

### Cons

- **A few hundred rows per run.** Unless it finds a registry to copy, a run stops at a few hundred rows: 146 to 341 local businesses, or 212 of a show's 3,194 exhibitors. DataForSEO returned 826 to 3,959 local businesses.
- **Slow for interactive work.** Agent runs took two to six minutes, and ultra's time limit can't go below five minutes.
- **Uneven contact data.** 97% of Dallas HVAC rows had a phone number, but 8% of NYC barbershops did, and 39% of Miami rows fell outside Miami-Dade.
- **Places search caps at 10.** Search returns at most 10 places per call. Wider lists mean splitting a city into ZIP codes yourself.

## Exa pricing

| Plan | Price | What you get |
| --- | --- | --- |
| Free credit | $10 a month | Resets on the 1st of each month. No subscription or minimum spend. |
| Search | $7 per 1,000 requests | Fast and auto search with up to 10 results; deep search $12, extra results $1 per 1,000. |
| Agent, fixed effort | $0.012 to $1.00 per run | Minimal, low, medium ($0.10), high and xhigh effort, each at a flat price. |
| Agent, auto and ultra | Metered | $0.10 per compute unit plus $0.005 per search, capped by a $1 to $100 budget per run. |
| Websets | Separate plan | Exa's list product, billed apart from API credit. |

- Ultra runs default to a $20 spending cap and $5 for auto; we used ultra with a $5 cap and a 10-minute limit.
- Contact enrichment inside an Agent run costs $0.02 per email and $0.07 per phone number.

Prices as of Oct 15, 2026, from https://exa.ai/pricing.

## Exa alternatives

- [pipe0 list-building search](https://pipe0.com/docs/search-catalog/research:exa/1): You want Exa's agent in a sheet or an MCP workflow, billed from Exa's own cost, with enrichment on the rows it returns.
- [DataForSEO](https://pipe0.com/reviews/dataforseo): You need local businesses by category: thousands of rows per city in seconds.
- [Crustdata](https://pipe0.com/reviews/crustdata): Filters can describe your companies, including the tech they use.
- [Parallel](https://pipe0.com/reviews/parallel): You need one researched answer per row rather than a new list.

## FAQ

### Can Exa build lead lists?

Yes, lists of a few hundred rows. Exa's Agent API turns a prompt into a structured list. In our tests an ultra run returned 146 to 341 local businesses per city in three to six minutes for about $1.10.

### Can Exa extract a full exhibitor list or directory?

No. On a trade show whose 3,194 exhibitors were public on one page, Exa returned 212 of them, 96% correct. To get every entry, use a tool that reads the directory page itself.

### How much does an Exa Agent run cost?

Fixed efforts cost $0.012 to $1.00 per run; medium is $0.10. Auto and ultra are metered at $0.10 per compute unit plus $0.005 per search, within a budget you set between $1 and $100. Our ultra runs cost $1.09 to $1.46.

### How many places does Exa search return?

In our tests, 10 places per search call, whatever numResults was set to. Exa recommends the Agent for longer lists.

### Exa or Parallel for building lists?

Exa. On four local business lists Exa's ultra agent returned more rows than Parallel's Task API every time, in three to six minutes against eight to fourteen.

### Exa or DataForSEO for local businesses?

DataForSEO. It returned two to six times Exa's rows in seconds, at $0.37 per 1,000. Exa found some businesses DataForSEO missed, so for a complete territory you can merge both.