An honest side-by-side look at ContractParser and Extracta.ai — where each one is stronger, and which to pick based on what you actually need.
Extracta.ai pricing and features verified June 8, 2026. Vendor terms change — check extracta.ai/pricing for current rates.
Extracta.ai and ContractParser share the same pricing model (pay-per-page, no subscription) and the same broad approach (LLM-based extraction, not the OCR-plus-templates stack at the low end of the market), but they target different buyers, run different pipelines under the hood, and disclose different amounts about what's actually doing the reading.
Extracta.ai is an API-first document extraction service aimed at developers. Send documents to the endpoint, define the fields you want, get structured JSON back. Designed to be integrated into your own application. Markets itself as “LLM Driven” without naming the model vendor. Offers a 50-page free trial, a pay-per-request plan, and custom-quote plans for higher volume (no per-page rate posted on its pricing page).
ContractParser is a polished web application aimed at non-developers — execs, legal ops, procurement, anyone with a pile of contracts who wants a spreadsheet. Drag-and-drop UI, field checklists, custom prompts, CSV output, direct Salesforce import. Runs Anthropic's Claude Sonnet 4.6 (Quick) and Claude Opus 4.7 (Verified, default) — named here and in our docs. $0.15/page Verified (audit pass included), $0.10/page Quick for bulk runs.
Both offer pay-per-use pricing instead of traditional SaaS subscriptions. Different buyers: if you're integrating extraction into a product you're building, Extracta's API is a reasonable choice. If you are the person with the contracts, ContractParser is built for you.
This is not an LLM-vs-OCR comparison the way the DigiParser or Docparser comparisons are. Both Extracta and ContractParser use large language models to do the actual reading and field extraction — neither is the cheaper OCR-plus-template-and-rules stack you'll find at the low end of this market. The gaps worth knowing are about which LLM and where OCR fits in the pipeline.
Extracta.ai describes itself as an “LLM Driven Solution” and mentions general OCR for image inputs (“OCR-powered data extractor platform”), suggesting a typical OCR-then-LLM pipeline where OCR pre-processes images into text and the LLM reads the text. They do not name a specific frontier-model vendor — no GPT, no Claude, no Gemini in their public messaging. That's a common pattern in this market; most vendors using third-party LLMs prefer to leave the choice opaque.
ContractParser runs Anthropic's Claude Sonnet 4.6 on the Quick tier and Claude Opus 4.7 on the Verified default tier — current-frontier reasoning models, named here and in our docs. There is no OCR engine in our pipeline. PDFs and images go directly to Anthropic's API; Claude's vision pathway reads the page itself, in the same pass as the reasoning. For text-native formats (DOCX, RTF, HTML, TXT), text is extracted with standard libraries and sent as text — those formats are already characters, not pixels, so there's nothing to OCR. The Verified audit pass is a second Opus run that re-reads the extraction and returns narrative reasoning on what it flagged.
Two practical effects fall out. On model disclosure: the effect is small if you're building an integration that just needs structured JSON — Extracta gets you that and you can swap providers later. The effect is larger if you're a buyer trusting the output directly: knowing the model is Opus 4.7 is informative in a way “LLM Driven” is not. On pipeline shape: OCR-then-LLM pipelines can compound errors — if OCR misreads “$1,200” as “$l,200” (a common OCR mistake on poor scans), the LLM only sees the bad string and has no access to the original page. A vision-LLM pipeline keeps the page in front of the model the whole time. The gap won't matter on clean text-native PDFs, but it shows up on scanned, photographed, or low-quality documents — exactly where extraction errors are most expensive.
Both tools avoid traditional fixed SaaS subscriptions, which is unusual in this market.
Extracta.ai: pay-per-request plan plus custom-quote plans for higher volume. Free trial includes 50 pages. Exact per-page or per-request rate isn't posted in a static pricing table on their site — third-party reviews report roughly $0.10/page; check extracta.ai/pricing for current rates.
ContractParser: $0.15/page Verified (default, audit pass included), $0.10/page Quick. No subscription. No monthly commitment. $2.00 minimum per batch. Full breakdown on the pricing page.
For small one-off workloads, Extracta's 50-page free trial and low-entry subscription both make it easy to try. For ongoing contract work, ContractParser's published per-page pricing makes cost-modeling simpler.
This is the real difference.
Extracta.ai is an API. To use it you write code: authenticate with an API key, send documents to an endpoint, parse the JSON response, wire it into your application. There's a web interface for testing, but the product is designed to be called programmatically. Their marketing says so explicitly (“seamless API integration,” “designed for developers”).
ContractParser is a web application. Open the site, drag a folder of contracts onto the upload area, pick fields from a checklist (or write a custom prompt), click Start. Results appear in a table you can sort, filter, and download as CSV. Also delivered by email. No code, no keys, no account required for first use.
Who the buyer is determines which matters. A developer building a legal tech product wants an API. An exec reviewing 100 vendor contracts before a renewal cycle wants a drag-and-drop tool.
Both tools use LLM-based extraction with strong accuracy on well-formatted documents. Where they diverge is on the verification step.
Extracta.ai returns structured JSON with extracted values. Their site references a validation process but doesn't expose field-level confidence or cross-field audit results in the public product documentation, and the model class doing the validation isn't disclosed.
ContractParser's Verified tier ($0.15/page, the default) runs a second Claude Opus 4.7 pass after the initial extraction. The audit pass catches contradictions between fields, flags math errors, checks that dates reconcile with the contract period, and returns narrative reasoning explaining what looks wrong.
A Verified flag looks like this:
totalValue calculation appears confused — mixes per-site, per-year, and portfolio figures inconsistently; $4,752/site/year × 4 sites × 10 years = $190,080, not $220,777.52.
For developers integrating extraction into a larger pipeline, a single confidence number per field is often enough — your application can route low-confidence extractions to human review. For a buyer working directly with the output, the audit pass explaining its concerns in plain language is more useful than a numeric flag — and it's running on a frontier reasoning model you can name.
Because ContractParser focuses on one document category, it ships with affordances a general-purpose tool won't have:
Extracta.ai is a general-purpose extraction API. It can be configured to extract any of these fields — it just doesn't come with contract-specific defaults or domain-aware verification logic.
Extracta.ai is positioned for a different buyer (developers integrating extraction into products) and does that job well at a fair price. They're one of the few competitors who, like us, charge per page rather than running a subscription with expiring credits — that's a real point of agreement on pricing philosophy. Where we differ is disclosure: we tell you the model is Claude Opus 4.7; they tell you it's an LLM.
We built ContractParser for the person with the contracts — the exec, legal ops, or procurement manager who needs answers by end of day and doesn't want to write code or call a developer. Different tool, different buyer.
If your job is “I'm building software that needs to extract data from documents,” try Extracta.ai.
Still weighing options? Our roundup of the 10 best contract parsers and document extraction tools places every major tool — Extracta.ai included — at the buyer and use case where it genuinely wins. Or browse other comparisons side-by-side.