Everything your agents need to know.

Conare searches all of your company's data and puts the right answer first. Built for accuracy, and measured on public benchmarks.

  • Documents
  • Files
  • Apps

How it works.

01

Connect

Write documents, upload files or connect an app. Each lands in a namespace.

02

Sync

A changed record replaces its old version. A deleted one is deleted.

03

Retrieve

Keyword and vector search find candidates. The reranker puts the best first.

04

Deliver

Your model gets the passages that answer the question, with their source.

Add a document. Query it.

Conare chunks, embeds and indexes on write, keeps your data updated in real time, and reranks every query.

$ npm install conare
import { Conare } from "conare";

const docs = new Conare().namespace("docs");
await docs.add({ text: "EU checkout broke after a key rotation." });
const [top] = await docs.query("why did checkout break?");
console.log(top.score, top.text);
0.91 EU checkout broke after a key rotation.

Everything retrieval needs, behind one key.

Sync

Keep your apps in a namespace.

Docs →

Embed

Embeddings for any vector database.

Docs →

Connect the apps your team already uses.

  • Gmail
  • Slack
  • Notion
  • Linear
  • GitHub
  • Granola
  • GCS
  • HubSpot
  • Salesforce
  • Attio
  • Affinity
  • Databases
  • and more

Nothing to run.

  • Servers, shards and index tuning
  • Embedding and reranking models
  • Sync jobs for every app
  • Separating each organization's data
  • Deleting a user: one call removes everything Conare holds of them

Accuracy you can check.

See every benchmark →

Read 14 October 2026. Comparator scores are what each vendor or leaderboard published, or our run of open weights where marked.

Most accurate, and the cheapest.

On ViDoRe v3, conare-embed-1 scores higher than every embedding API on this chart and costs less per token than each of them.

See the benchmark →
56606468$0.05$0.10$0.20$0.50$1.00$2.00up and to the left is betternDCG@10price per 1M tokens, log scaleconare-embed-1voyage-4-largegemini-embedding-2Cohere embed-v4.0Mixedbread
List prices per 1M text tokens, each model at its best score. Mixedbread publishes no embedding price; its $1.50 is indexing per 1M content tokens. Perplexity's open 9B has no API price, so it isn't plotted.

See it on your own data.