“We were scaling document volume by nearly 50 percent every month —
Nutrient handled it without us adding resources.”
Harvey
compare
Nutrient is a Reducto alternative for document extraction and retrieval-augmented generation (RAG). This feature-by-feature comparison shows where Nutrient wins — a full document platform, deterministic grounding, cheaper text and structure parsing, and a free tier that renews every month — and where Reducto has the edge.
| Nutrient | Reducto | |
|---|---|---|
| Core approach | An owned, hybrid OCR + AI pipeline (text, structure, understand,
agentic) you tune per document. Repeatable, rule-based output you
control. | An agentic multipass platform — a layout model, vision language
models (VLM), and a self-correcting optical character recognition
(OCR) loop. Excellent on complex tables; output leans on VLM
inference. |
| Scope | ||
| Output formats | ||
| Deployment |
Nutrient is a single deterministic document platform: the same extraction layer, plus the viewers, editors, and signing your users actually work in — on web, mobile, and server.
Reducto is a focused, excellent agentic extraction platform — parse, extract, split, classify, and fill forms. But once your application also needs to view, annotate, redact, sign, compare, or convert those documents, that’s a second vendor.
Nutrient runs an owned, rule-based pipeline that returns repeatable output for the same page on its non-VLM modes — with a per-field confidence signal and an interpretable match label (exact, fuzzy, or not found) your review logic can branch on. Because that pipeline is deterministic, its accuracy benchmarks are open and reproducible: a public test set, every parser pinned to its latest version, re-scored on each commit rather than a one-time vendor claim.
Reducto leans on vision language models with an agentic self-correction loop — returning the best extraction it can find, including self-correcting when confidence is low.
Reducto markets state-of-the-art table accuracy on its own RD-TableBench. Nutrient’s numbers are published on the open OpenDataLoader benchmark — here’s how it scores.
| OpenDataLoader benchmark | Nutrient |
|---|---|
| Overall accuracy (standard engine) | 0.889 |
| Reading order (NID) | 0.926 |
| Table structure (TEDS, standard engine) | 0.739 |
| Speed per page | 0.004s — 134× faster than Docling |
Scores from the independent OpenDataLoader benchmark (opendataloader.org), an open, reproducible evaluation of document parsers on a public, hand-annotated corpus; figures as published in 2026 and subject to change as the benchmark re-runs. Reducto is not evaluated in this benchmark — these are Nutrient’s own published results, not a head-to-head.
An honest, capability-by-capability comparison — including where Reducto wins.
| Nutrient | Reducto | Winner | |
|---|---|---|---|
| Complex table extraction | Handled by understand and agentic modes. | A core focus — agentic OCR with math-invariant self-correction;
state-of-the-art on its RD-TableBench. | Reducto |
| Agentic OCR/self-correction | VLM-augmented agentic mode for the most difficult documents. | Iterative verification loops with checksum and math-invariant
validation on dense financials. | Reducto |
| Schema extraction and citations | The /extract endpoint maps to your JSON Schema with per-field
citations and match labels. | Extract and Deep Extract map to a JSON Schema with spatial
citations. | Draw |
| Deterministic, rule-based output | Owned hybrid OCR and AI pipeline; repeatable, auditable output
with interpretable match labels. | VLM-driven with an agentic correction loop; output depends on
model inference. | Nutrient |
| Form filling/writeback | Form filling and full editing in the Nutrient viewer and SDKs. | Edit API fills fields and templates from natural language
instructions, auto-detecting checkboxes. | Different approaches |
| On-premises/self-hosted | Self-host the extraction engine via the SDKs and Document Engine. | Private VPC and air-gapped on-premises deployments. | Draw |
| Security and compliance | SOC 2 Type 2 audited; transport layer security (TLS)-encrypted
transport. | SOC 2 Type 2, HIPAA, zero-data retention option. | Draw |
| Output formats | Spatial JSON, Markdown, and schema JSON from one API. | JSON, Markdown, HTML tables, and schema JSON. | Draw |
| Full document platform | View, edit, redact, sign, compare, and convert — beyond
extraction. | Extraction and form writeback only. | Nutrient |
| Cross-platform SDKs | SDKs for web, mobile, and server, plus a Model Context Protocol
(MCP) server. | Server SDKs (Python, Node.js, Go), a CLI, and an MCP server. | Nutrient |
| Developer experience for AI teams | Documentation, SDKs, MCP, and a growing set of connectors. | Reducto Studio’s visual verification and a focused, AI-team-first
workflow. | Reducto |
| Per-page price | Monthly plans include credits; published overage rates are
$0.0012/credit on Pro and $0.0028/credit on Starter. | Standard rates start at $10/1,000 pages for r-1 Parse, $20 for
Extract, and $40 for Deep Extract; legacy parse modes and add-ons
have separate rates. | Depends on mode |
Reducto stops at extraction and form writeback. Nutrient is a full document platform, so the same vendor also powers the human-facing document work your application needs — no second integration, no second contract.
| Nutrient | Reducto | |
|---|---|---|
| Document viewer and rendering | ||
| Annotations and markup | ||
| Redaction | ||
| eSignatures | ||
| Document comparison | ||
| Conversion and generation | ||
| Mobile SDKs | ||
| Accessibility |
These rates cover document extraction — parsing and schema extraction. The two vendors bill differently: Reducto publishes Standard rates by product and parse model, while Nutrient’s monthly plans include a credit allowance and publish per-credit overage rates. The table estimates Nutrient’s post-quota cost using its monthly Pro and Starter overage rates. On that basis, text and structure parsing costs several times less; schema and agentic extraction depend on the Nutrient mode and plan. Here’s roughly what 1,000 pages costs.
| Nutrient | Reducto | |
|---|---|---|
| Free usage | 5,000 credits every month | $150 once (15,000 credits) |
| Parse — text and structure | ~$1.20–$4.20/1,000 pages | $10/1,000 pages for r-1; legacy parse is $15–$30 |
| Parse — understand and agentic | ~$10.80–$50.40/1,000 pages | $10/1,000 pages for r-1; legacy agentic parse is $30–$60 |
| Schema extraction — understand | ~$18–$42/1,000 pages | $20/1,000 pages (Extract) |
| Agentic and deep extraction | ~$28.80–$67.20/1,000 pages | $40/1,000 pages (Deep Extract) |
| Classification | ~$1.20–$2.80/1,000 pages | $7.50/1,000 pages |
Published self-serve rates as of 11 September 2026, shown per 1,000 pages. Reducto Standard rates are r-1 Parse $10, legacy Parse $15 for standard and $30 for complex pages (doubled in agentic modes), Extract $20, Deep Extract $40, and Classify $7.50. Optional OCR, region, and chart add-ons cost extra; Extract and Deep Extract include parsing, dense extractions with more than 100 fields per page may add a surcharge, and batch Parse and Extract are 20 percent cheaper. Reducto describes its introductory allowance as $150 in free usage and 15,000 free credits. Nutrient estimates use monthly overage after included credits: $0.0012/credit on Pro ($500/month with 500,000 included credits) and $0.0028/credit on Starter ($59/month with 25,000 included credits). Formula: credits/page × 1,000 × rate. Parse uses 1 credit for text, 1.5 for structure, 9 for understand, and 18 for agentic; Extract totals 7, 7.5, 15, or 24 credits; Classify uses 1. Annual rates are lower and are not used in this table. These rates cover the Data Extraction API only; the viewer, editing, signing, and other SDK capabilities above are licensed separately.
Parse and extract. Then view, edit, redact, sign, compare, and convert across one platform. Reducto stops at extraction and form writeback.
Text and structure parsing runs several times under Reducto’s $10 per 1,000 pages, and the free tier renews every month instead of once.
A rule-based pipeline returns repeatable output for the same page, with per-field confidence and interpretable match labels built for audits.
SDKs for web, mobile, and server, plus an MCP server — so the same document stack ships in the app, not just the pipeline.
5,000 Data Extraction API credits every month, no credit card required. Pick the cheapest mode that meets your accuracy bar.
Reducto is an agentic document platform for AI teams. It parses, extracts, splits, classifies, and fills forms through a REST API and SDKs using a multipass pipeline (layout model, vision language models, and a self-correcting OCR loop). It’s known for state-of-the-art complex-table extraction and offers cloud, VPC, and air-gapped on-premises deployment.
Yes, for many teams — especially if you need more than extraction or want a lower entry cost. Nutrient is a full document platform (parse and extract, plus viewing, editing, redaction, signing, comparison, and conversion across web, mobile, and server SDKs) with deterministic, source-grounded output, parsing that costs several times less in text and structure modes at its published monthly overage rates, and a free tier that renews every month. Schema and agentic extraction depend on the Nutrient plan and mode. Reducto has the edge on complex-table accuracy and agentic OCR self-correction, so weigh it by how table-dense your documents are.
If you’re comparing Reducto with other document extraction and parsing tools, the main alternatives are Nutrient, LlamaParse and LlamaExtract, Unstructured, Docling, Mistral Document AI, and Azure Document Intelligence. Nutrient stands out as a full document platform — extraction plus viewing, editing, signing, and conversion — with deterministic grounding, cheaper text and structure parsing, and a free tier that renews every month.
Both produce layout-aware, citable output for RAG. Reducto is the stronger choice when your corpus is dominated by dense, complex tables that need agentic OCR. Nutrient is the better fit when you want structured Markdown across content-heavy documents, deterministic output you can audit, a single platform that also views and edits documents, and cheaper parsing in the text and structure modes. Many teams pick Nutrient for the breadth and the entry cost and reserve a specialist only for their most difficult table workloads.
Since 1 September 2026, Reducto’s Standard rates are $10 per 1,000 pages for r-1 Parse, $20 for Extract, $40 for Deep Extract, and $7.50 for Classify; parsing is included in Extract and Deep Extract. Its introductory allowance is $150 in free usage, which Reducto also describes as 15,000 free credits. Nutrient bills credits per page — 1 for text parsing, 1.5 for structure, 9 for understand, and 18 for agentic, with schema extraction adding 6 credits per page — and 5,000 free credits arrive every month. Using Nutrient’s published monthly overage rates of $0.0012/credit on Pro and $0.0028/credit on Starter, text and structure parsing costs several times less than Reducto’s $10 per 1,000 pages; schema and agentic extraction vary by mode and plan. Talk to our team for a comparison scoped to your workload.
Yes — both vendors support self-hosting. Nutrient’s parsing and extraction can be self-hosted through its SDKs and Document Engine, and Reducto offers private VPC and air-gapped on-premises deployments. If on-premises is a hard requirement, both are viable; the deciding factors are usually platform breadth and cost.
Yes. The Data Extraction API is the parsing layer of a full document platform. Connect its output to AI Document Processing for templates and validation; to DWS for conversion, redaction, generation, and signing; and to Nutrient SDKs when humans need to review, edit, annotate, or approve documents in your application. Reducto focuses on extraction and form writeback.
EXPLORE
Unstructured.io is a strong RAG-ingestion toolkit — open source partitioning, chunking, and a deep connector ecosystem. Nutrient adds what it doesn’t: grounded schema extraction and the full document lifecycle — viewing, editing, signing, and conversion.
LlamaIndex’s LlamaParse and LlamaExtract are cloud-first — self-hosted BYOC is gated to Enterprise plans — and lean on foundation model inference. Nutrient delivers deterministic, source-grounded extraction, self-hosted on any plan, and a viewer to verify every citation.
Amazon Textract is a mature AWS OCR and document-extraction service — but it runs only inside AWS and returns a raw block graph that must be reassembled manually. Nutrient extracts in the cloud or fully self-hosted, in 100+ languages, with LLM-ready structured output and grounded, benchmarked accuracy.
5,000 free Data Extraction API credits per month — no credit card required. Parse and extract source-grounded data your AI workflows can trust, on one platform.