Reducto is the complete agentic document platform for AI teams building on top of frontier models. If your team is weighing Cohere's document processing against Reducto, the framing worth holding in mind is that these address different layers of the problem. Cohere is a foundation-model vendor with a semi-custom document parser layer. Reducto orchestrates 12+ models — including frontier models from foundation-model vendors — and adds the layout parsing, deterministic extraction, citation regions, and cost controls that turn model output into production-grade document infrastructure.

This page is for engineering leaders at enterprises who already know Cohere as a trusted AI vendor and are trying to decide whether the document layer they get there is enough for their production workflow.

What Cohere document processing is genuinely strong at

Cohere brings real strengths to enterprise document evaluations. The enterprise-facing brand carries weight in procurement — Cohere is a known, trusted AI vendor with established commercial relationships and security posture. For buyers who value vendor familiarity, that's a meaningful advantage when narrowing a vendor list.

There's a semi-custom parser layer on top of the model, which is more document-oriented than calling a horizontal LLM directly. No template training is required, so a team can point Cohere at a new document type and start experimenting without setup overhead. On straightforward text-centric tasks, the platform performs well — foundation-model vendors typically have strong baseline text understanding, and Cohere fits that pattern.

The single-vendor story matters for some buyers, too. One AI vendor across multiple workloads simplifies procurement, billing, and integration maintenance. Enterprises that already standardize on Cohere for embeddings, retrieval, or generation often want to add documents to that footprint as the path of least resistance.

If your need is for an enterprise AI vendor with some document functionality, and vendor familiarity outweighs document-specific depth, Cohere document processing is a reasonable starting point.

Where the production gap shows up

The gap appears when "trusted AI vendor with a parser layer" needs to become "production document platform." Cohere's parser adds structure on top of the model, but it isn't framed as document-native in the way that production workflows often require.

Layout depth. The semi-custom parser layer helps relative to a raw foundation model, but it isn't positioned as layout-leading. Complex reading order on dense pages with many blocks — multi-column layouts, sidebars, footnotes, embedded tables — is where general parser layers tend to struggle without document-native architecture underneath.

Coordinate-level citations. There's no evidence that Cohere document processing solves the kind of sub-region citation and layout return that production workflows require. For regulated environments where every extracted field needs a bounding box on the source page, this is usually a hard requirement, not a nice-to-have.

Determinism. Some parser structure helps relative to a generic LLM call, but the architecture isn't described as deeply deterministic. The same document run twice can produce different outputs, which complicates evaluation and audit trails — exactly the workflows enterprise procurement cares about.

Dense structured data. The semi-custom parsing layer may help on tables and structured content, but it isn't presented as document-native model training. Under output-token pressure, the underlying model can still compress rows or drop detail rather than returning the full table faithfully.

Charts, checkboxes, handwriting. These are the page elements where evidence of head-to-head document-specific strength tends to be thinnest from foundation-model vendors. Without independent benchmarks, the claim is "general capability inherited from the model," not "purpose-built document depth."

How Reducto fits alongside Cohere

Reducto is not a replacement for Cohere the model vendor. Reducto is the production layer that sits between your application and the right model for each page. The platform orchestrates 12+ models, including frontier and foundation-vendor models, and decides on a per-page basis which to call.

On top of model orchestration, Reducto adds the layer that's missing when you call a foundation-model document SKU directly:

Layout parsing built for complex reading order, multi-column pages, and dense structured content.
Schema-driven extraction that adapts to new document types without retraining or re-labeling.
Sub-page citation regions with bounding boxes — every extracted field traces back to a coordinate on the source page.
Cost control via routing, configurable accuracy/latency/throughput trade-offs, and per-page pricing that's predictable in advance.
Multi-pass agentic VLM workflows with self-correction for hard pages, rather than single-shot guessing.
30+ filetypes beyond PDF, including spreadsheets, slides, and scanned formats.

A critical property: Reducto stays model-agnostic. As foundation-model vendors release stronger models, Reducto's pipelines benefit without your team rewriting integrations. You inherit the upside of model progress without committing your document workflow to a single vendor's roadmap.

When to reach for Cohere alone

There are real scenarios where a single enterprise AI vendor's document layer is the right call. Teams that already run Cohere for embeddings, generation, or retrieval and want to consolidate documents into the same footprint. Workflows where document complexity is low and procurement consolidation is the primary driver. Buyers who weight vendor familiarity higher than document-native depth. Use cases where the cost of occasional output drift is also low.

If you're in one of those scenarios, going direct to Cohere document processing is a reasonable call.

When to reach for Reducto

The pattern shifts in production. AI workflows running at enterprise scale where outputs need to be deterministic and citations are non-negotiable. Per-page cost that has to be predictable for budgeting and unit economics. Regulated environments demanding SOC 2, HIPAA, and zero data retention. Document corpora spanning 30+ filetypes, not just clean PDFs. Teams that want to ship AI features instead of maintaining ingestion infrastructure.

Reducto is trusted by Harvey, Scale AI, and Vanta for exactly this kind of work — production AI on messy real-world documents at enterprise scale. The pattern across those teams is consistent: they needed document depth and citations that vendor-familiar AI platforms don't provide out of the box, and they wanted the option to use the best model for each task rather than commit to a single foundation-model vendor's roadmap.

On benchmarks

Every vendor publishes benchmarks that show their product winning, and Reducto is no exception. The honest stance is that vendor benchmarks — Reducto's included — carry bias, and the only evaluation that matters is the one run on your own documents. Reducto's free tier exists so teams can do that head-to-head comparison against Cohere document processing, or any other tool, on the documents they actually care about.

Reducto wins where proof, depth of extraction, and document-native architecture matter more than vendor familiarity.