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<title>HyperAPI by Hyperbots: Document intelligence APIs for finance</title>
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<header class="hero">
  <div class="wrap">
    <span class="badge">HyperAPI · by Hyperbots</span>
    <h1>Turn financial documents into validated JSON</h1>
    <p class="lede">HyperAPI is a set of document intelligence APIs for invoices, receipts, bank statements, contracts and other finance documents. You send a PDF or image and get back clean text, typed fields, a document type or redacted pages. It works from a backend service, a dashboard or an AI agent.</p>
    <div class="cta">
      <a class="btn primary" href="https://apis.hyperbots.com/dashboard/register" target="_blank" rel="noopener">Get a free API key</a>
      <a class="btn ghost" href="https://apis.hyperbots.com/docs" target="_blank" rel="noopener">Read the docs</a>
      <a class="btn ghost" href="https://apis.hyperbots.com/sandbox" target="_blank" rel="noopener">Try the sandbox</a>
    </div>
    <div class="facts">
      <div><b>5</b>core endpoints</div>
      <div><b>30 pages / mo</b>free, no credit card</div>
      <div><b>$0.001 / page</b>fast parse</div>
      <div><b>Python SDK</b>sync + async, MIT</div>
    </div>
  </div>
</header>

<section>
  <div class="wrap">
    <h2>Five endpoints. Call any of them on its own.</h2>
    <p class="sub">Each endpoint takes a <code>document_key</code> from a single upload, so you can chain them without uploading the file again.</p>
    <div class="grid">
      <div class="card"><h3>Parse</h3><code>POST /v1/parse</code><p>OCR to clean text and markdown with page geometry, line and word boxes, layout regions and table parsing. <code>advanced</code> mode adds per-page structured HTML and markdown.</p><div class="price">from $0.001 / page</div></div>
      <div class="card"><h3>Extract</h3><code>POST /v1/extract</code><p>Typed entities and line items from invoices and receipts. For any other document, pass your own JSON schema.</p><div class="price">$0.05 / page</div></div>
      <div class="card"><h3>Classify</h3><code>POST /v1/classify</code><p>Returns a document type with a confidence score and ranked candidates. You can add your own classes and descriptions.</p><div class="price">$0.05 / page</div></div>
      <div class="card"><h3>Split</h3><code>POST /v1/split</code><p>Breaks a bundled PDF into separate logical documents, with a page range, label and confidence for each.</p><div class="price">$0.05 / page</div></div>
      <div class="card"><h3>Redact</h3><code>POST /v1/redact</code><p>Covers PII with black boxes or replaces it with synthetic values. You can add your own entity types.</p><div class="price">$0.05 / page</div></div>
    </div>
  </div>
</section>

<section class="alt" id="quickstart">
  <div class="wrap">
    <h2>Quickstart</h2>
    <p class="sub">Python 3.9+. The official SDK installs from GitHub.</p>
    <ol class="steps">
      <li>Create a free account and generate a key at <a href="https://apis.hyperbots.com/dashboard/api-keys" target="_blank" rel="noopener">apis.hyperbots.com/dashboard/api-keys</a>. Keys that start with <code>hk_live_</code> are for production and keys that start with <code>hk_test_</code> are for testing.</li>
      <li>Install the SDK and set <code>HYPERAPI_KEY</code>.</li>
      <li>Parse and extract in a single call.</li>
    </ol>
<pre><span class="c"># install (the package installs as hyperapi-sdk and imports as hyperapi)</span>
pip install <span class="s">"hyperapi-sdk @ git+https://github.com/hyprbots/hyperapi-sdk.git"</span>
export HYPERAPI_KEY=hk_test_...</pre>
<pre><span class="k">from</span> hyperapi <span class="k">import</span> HyperAPIClient

<span class="k">with</span> HyperAPIClient() <span class="k">as</span> client:          <span class="c"># reads HYPERAPI_KEY</span>
    doc = client.process(<span class="s">"invoice.pdf"</span>)      <span class="c"># parse + extract in one call</span>
    print(doc[<span class="s">"result"</span>])

    text  = client.parse(<span class="s">"invoice.pdf"</span>)            <span class="c"># OCR text + layout</span>
    kind  = client.classify(<span class="s">"bundle.pdf"</span>)          <span class="c"># document type + confidence</span>
    parts = client.split(<span class="s">"bundle.pdf"</span>)             <span class="c"># page ranges per document</span>
    safe  = client.redact(<span class="s">"statement.pdf"</span>, mode=<span class="s">"deidentify"</span>)</pre>
    <div class="note">Don't run <code>pip install hyperapi</code>. That name on PyPI belongs to an unrelated project. Use the GitHub install above.</div>
    <p>For FastAPI, aiohttp or agent loops, use <code>AsyncHyperAPIClient</code> and fan calls out with <code>asyncio.gather</code>. Every endpoint also has a <code>submit_*</code> variant that returns a job for bulk or long-running work. Batches are available through <code>create_batch_from_files</code>.</p>
  </div>
</section>

<section id="rest">
  <div class="wrap">
    <h2>REST, from any language</h2>
    <p class="sub">The flow has three steps: request an upload URL, PUT the bytes, then call any endpoint with the <code>document_key</code>. The key is valid for 24 hours.</p>
<pre><span class="c"># 1. request a presigned upload URL</span>
curl -X POST https://apis.hyperbots.com/v1/documents/upload \
  -H <span class="s">"X-API-Key: $HYPERAPI_KEY"</span> -H <span class="s">"Content-Type: application/json"</span> \
  -d <span class="s">'{"filename":"invoice.pdf","content_type":"application/pdf","content_length":184213}'</span>
<span class="c"># -> {"document_key":"550e8400-...","upload_url":"https://...","expires_in":900}</span>

<span class="c"># 2. upload the file to upload_url with an HTTP PUT (no API key needed)</span>

<span class="c"># 3. extract structured fields</span>
curl -X POST https://apis.hyperbots.com/v1/extract \
  -H <span class="s">"X-API-Key: $HYPERAPI_KEY"</span> \
  -F <span class="s">"document_key=550e8400-e29b-41d4-a716-446655440000"</span></pre>
    <div class="two">
<pre>{
  <span class="s">"status"</span>: <span class="s">"success"</span>,
  <span class="s">"task"</span>: <span class="s">"extract"</span>,
  <span class="s">"model_used"</span>: <span class="s">"HyperLM"</span>,
  <span class="s">"result"</span>: {
    <span class="s">"entities"</span>: {
      <span class="s">"invoice_number"</span>: <span class="s">"INV-2024-0042"</span>,
      <span class="s">"date"</span>: <span class="s">"2024-01-15"</span>,
      <span class="s">"due_date"</span>: <span class="s">"2024-02-15"</span>,
      <span class="s">"vendor_name"</span>: <span class="s">"Acme Supplies Ltd"</span>,
      <span class="s">"total_amount"</span>: <span class="s">"1,250.00"</span>,
      <span class="s">"currency"</span>: <span class="s">"USD"</span>
    },
    <span class="s">"line_items"</span>: [ ... ]
  }
}</pre>
<pre><span class="c"># any document, your schema</span>
curl -X POST \
 <span class="s">"https://apis.hyperbots.com/v1/extract?category=non_financial"</span> \
 -H <span class="s">"X-API-Key: $HYPERAPI_KEY"</span> \
 -F <span class="s">"document_key=..."</span> \
 -F <span class="s">'schema={"patient_name":null,"active":false}'</span>

<span class="c"># dense tables and forms</span>
<span class="c"># add ?parse_mode=advanced (Plus, Pro, Custom)</span>

<span class="c"># process asynchronously and get a job id</span>
-H <span class="s">"X-Async: true"</span></pre>
    </div>
  </div>
</section>

<section class="alt" id="pricing">
  <div class="wrap">
    <h2>Pricing</h2>
    <p class="sub">Start free. Paid plans charge overage to prepaid credits at the per-page rates shown above. Results are cached per document for 24 hours, and cached results are not billed.</p>
    <table>
      <tr><th>Plan</th><th>Price</th><th>Pages / month</th><th>Rate limit</th><th>Highlights</th></tr>
      <tr><td><b>Free</b></td><td>$0</td><td>30</td><td>1 req/min</td><td>All core APIs, fast parse, no credit card</td></tr>
      <tr><td><b>Starter</b></td><td>$1</td><td>300</td><td>10 req/min</td><td>Core APIs, email support</td></tr>
      <tr><td><b>Plus</b></td><td>$25</td><td>10,000</td><td>30 req/min</td><td>Advanced parse, team workspace with 3 seats</td></tr>
      <tr><td><b>Pro</b></td><td>$99</td><td>50,000</td><td>60 req/min</td><td>Priority routing, up to 10 seats, priority support</td></tr>
      <tr><td><b>Custom</b></td><td>Talk to us</td><td>Volume</td><td>Dedicated</td><td>BYOK, IP allowlist, human-in-the-loop review</td></tr>
    </table>
    <p style="margin-top:14px;color:var(--muted);font-size:14.5px">Current prices and promotions are on the <a href="https://apis.hyperbots.com/pricing" target="_blank" rel="noopener">pricing page</a>.</p>
  </div>
</section>

<section id="details">
  <div class="wrap two">
    <div>
      <h2>Inputs and limits</h2>
      <ul class="clean">
        <li>PDF, PNG, JPEG, WebP, TIFF and HEIC, plus Word, Excel, PowerPoint, CSV, TXT, RTF, JSON and XML.</li>
        <li>Uploads up to 50 MB (512 MiB for Custom async).</li>
        <li>Fast parse, Classify and Split have no page cap. Advanced parse and advanced Extract allow 60 pages (500 for Custom async). Redact allows 36 pages.</li>
        <li><code>GET /v1/limits</code> returns the limits that apply to your key.</li>
      </ul>
    </div>
    <div>
      <h2>Data handling</h2>
      <ul class="clean">
        <li>Files are processed in memory and deleted when a run completes, unless you turn on retention.</li>
        <li>Documents are not used for training.</li>
        <li>Redact can remove PII before any downstream model sees the document.</li>
        <li>Hyperbots is SOC 1 Type 2, SOC 2 Type 2 and ISO 27001 certified.</li>
      </ul>
    </div>
  </div>
</section>

<section class="alt" id="research">
  <div class="wrap">
    <h2>Research behind it</h2>
    <p class="sub">HyperAPI runs on Hyperbots' finance-specific models, including HyperLM and in-house vision-language models.</p>
    <div class="grid">
      <div class="card"><h3>DocuLite</h3><p>Adapting LLMs and VLMs to invoice extraction without human-annotated training data, using synthetic data generators (InvoicePy and TemplatePy). Accepted at the 4th Deployable AI Workshop, AAAI 2026.</p><p><a href="https://www.hyperbots.com/research/breaking-the-annotation-barrier-with-doculite" target="_blank" rel="noopener">Read the research →</a></p></div>
      <div class="card"><h3>Synthetic invoice dataset</h3><p>A synthetic invoice set with HTML, OCR-style text and gold labels in the Extract output format. Use it to benchmark HyperAPI or your own pipeline.</p><p><a href="https://huggingface.co/datasets/hyperbots-inc/synthetic-invoice-extraction" target="_blank" rel="noopener">Open the dataset →</a></p></div>
      <div class="card"><h3>Engineering blog</h3><p>Posts on deterministic extraction from financial PDFs, schema-as-contract, and classifying more than 1,400 bank statement templates.</p><p><a href="https://apis.hyperbots.com/blogs" target="_blank" rel="noopener">Read the blog →</a></p></div>
    </div>
  </div>
</section>

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