Exa vs Parallel for finding similar companies (lookalike APIs), benchmarked
Both Exa and Parallel return companies that resemble a seed account — Exa via neural company search from a seed-anchored capability query, Parallel via agentic entity search from the same seed-anchored query as Exa. Here is how they compare on identical B2B seed companies, scored by the same three-model LLM judge panel.
Exa vs Parallel, scored on the same seeds
Same input, same judge, same seed companies — so the gaps below reflect relevance, not different test sets. See the full methodology and matrix →
| Metric | Exa | Parallel | Winner |
|---|---|---|---|
| Precision@10 (top-of-list quality) | 80.8% | 69.2% | Exa |
| Precision@100 (long-list quality, headline) | 48.6% | 56.9% | Parallel |
| Relevant companies returned | 2,331 | 2,675 | Parallel |
How Exa and Parallel find lookalikes
Exa surfaces lookalikes via neural company search from a seed-anchored capability query; Parallel via agentic entity search from the same seed-anchored query as Exa. Same seed, same top-K, same LLM judge — so the mechanism difference shows up directly in the relevance numbers above.
Agent sign-up and use instructions
How an agent runs a lookalike / company search on each — the access model (does the agent get in on its own, or does a human?), the exact call, and the credits.
POST api.exa.ai/search · category: companykey
POST /v1beta/findall/entity-searchkey · free tierComparing other vendors? See the full benchmark → ·