IDP Forge vs. Reducto vs. LandingAI: Which Is the Best Document Extraction API?

Infrrd’s IDP Forge, Reducto, and LandingAI are document extraction APIs built to turn unstructured PDFs, scans, and forms into structured, machine-readable data. On the surface, they look similar. All three offer data extraction, parsing, document splitting, and JSON output for downstream systems.

The differences that matter to developers and data teams appear beneath the surface. Does the platform route work across multiple LLMs or lock users into one model? Can developers bring their own model keys? Can teams test extraction accuracy before deployment? Can the platform pass an enterprise security and compliance review? Most importantly, how does it handle data security, compliance, and data sovereignty?

In this blog, we break down the features of all three tools and leave the final judgement to you.*

IDP Forge is Infrrd’s developer-first extraction API. It is built on Infrrd’s core platform, which has more than 10 years of enterprise IDP deployment experience and has processed over 10 billion pages. Its core architecture is multi-model. It can route each pipeline stage, such as layout analysis, OCR, table extraction, and classification, to the LLM best suited to that task. It also allows developers to bring their own provider keys from OpenAI, Anthropic, or Google, keeping billing and data agreements in-house.

Reducto is a newer, developer-focused platform with a no-code visual pipeline builder, agentic self-correction, and multi-region SaaS deployment. It runs extraction through a single, vendor-managed pipeline rather than routing work across multiple models.

LandingAI is built around a single proprietary extraction model. It covers the fundamentals of confidence scoring and source provenance, but it does not offer multi-model routing, BYOK, or several of the production features available in the other two platforms.

This comparison examines each platform’s architecture, traceability, workflow features, evaluation tools, deployment options, and pricing model in detail.

Model Architecture: Multi-Model Routing vs. Single Proprietary Pipelines

This is the biggest structural difference between the three platforms, and it is worth examining separately.

Reducto and LandingAI run every document through one model or vendor-managed pipeline. That model may be well-tuned for general extraction, but the platform’s accuracy ceiling is limited by what that model can do across every document type and field, regardless of whether it is the best tool for a specific task.

IDP Forge is built differently. Each stage of the pipeline can be routed to a different model: GPT-4o for layout understanding, Claude for complex tables, Gemini for classification, or another combination selected by the developer.

Developers are not locked into one vendor’s strengths and blind spots. They can combine models at different stages to find the best balance of accuracy and cost for their documents.

This flexibility also extends to pricing and data control through BYOK, or bring your own key.

IDP Forge allows developers to route requests through their own OpenAI, Anthropic, or Google API keys. This means existing data-processing agreements remain in place, and there is no hidden LLM markup built into per-page pricing.

Neither Reducto nor LandingAI offers this option. Both keep processing within their own managed pipelines, meaning billing and data terms are controlled by the vendor.

Traceability and Confidence Scoring

All three platforms provide confidence scores and source provenance at some level, but the depth of those capabilities differs.

IDP Forge connects every extracted field to a confidence score, bounding box, page reference, and complete field-level provenance. It also applies automatic page rotation so that skewed or rotated scans do not silently reduce extraction quality.

Reducto offers similar capabilities, including confidence scores, source provenance, bounding boxes, page citations, and automatic page rotation.

LandingAI provides confidence scores, bounding boxes, and page citations, but it does not apply automatic page rotation. As a result, misaligned scans may be more likely to produce extraction errors that confidence scores alone may not catch.

Workflow Completion and Self-Learning

Extraction is only part of most production document workflows. Incomplete forms, blank cells, and unchecked boxes may still need to be resolved before the data becomes usable.

IDP Forge and Reducto both offer an Edit API that can fill blank fields, checkboxes, dropdowns, and table cells.

IDP Forge’s Edit API works across PDFs and DOCX files, while Reducto's API fills forms in the original document.

LandingAI does not offer an equivalent capability. Its workflow stops at extraction, so incomplete-field resolution must take place outside the platform.

For continuous improvement, IDP Forge provides a Feedback API and continuous learning module. Every verified correction made by a reviewer feeds back into the system, helping improve accuracy over time.

Reducto's agentic correction aims to achieve a similar result through a different mechanism.

LandingAI as a limited feedback loop, meaning accuracy improvements depend more heavily on manual retraining than on a built-in continuous learning process.

Predeployment Evaluation

Before putting a document extraction platform into production, teams need to know how accurately it performs on their documents, not only on examples selected by the vendor.

IDP Forge allows teams to upload ground-truth datasets and run precision, recall, F1, and confusion-matrix evaluations before deployment. Teams can also compare models side by side in its Visual Studio.

Reducto provides a comparable Studio evaluation mode.

LandingAI does not provide a no-code studio or built-in ground-truth evaluation tools. Accuracy testing before deployment must therefore be handled manually outside the platform.

Deployment, Integration, and Scale

Deployment flexibility is one area where Reducto closes some of the gap with IDP Forge.

Reducto supports multi-region SaaS deployment in the US and EU, along with VPC and on-premises deployment. This can be useful for teams with specific data-residency requirements.

IDP Forge supports SaaS, VPC, and on-premises deployment, but it does not currently list the same multi-region SaaS coverage.

For integrations, IDP Forge offers the widest range of options: SDKs, REST APIs, CLI, Postman collections, and prebuilt connectors.

Reducto provides SDKs, REST APIs, a playground, and MCP support, but it does not offer a CLI, Postman collections, or connectors.

LandingAI does not publish details about its integration tooling at the same level.

For scale, IDP Forge is the only platform among the three with a stated throughput figure. It is built to process more than 10 million pages per day and is backed by a core platform that has processed over 10 billion pages.

Neither Reducto nor LandingAI publishes a throughput figure.

Enterprise Credibility and Compliance

For teams that need to defend a vendor decision to procurement, security, or compliance stakeholders, third-party validation matters.

IDP Forge’s core IDP engine is recognised as a Leader by Gartner and Everest Group. It holds more than 12 granted patents and has over 10 years of enterprise deployment experience, along with SOC 2 and GDPR compliance.

Reducto has several named start-up customer logos but is not currently listed in major analyst reports or patent filings.

LandingAI is in a similar position and is not currently listed in major analyst reports or patent filings.

Pricing and Uptime

IDP Forge and Reducto publish similar pricing structures, including free tiers, pay-as-you-go pricing, subscriptions, and enterprise plans.

Reducto also advertises volume discounts.

LandingAI does not publish pricing information at the same level of detail.

For uptime, IDP Forge states a 99.95% SLA, while Reducto states an SLA of more than 99.9%.

LandingAI does not publish an SLA figure.

When to Choose Each Platform

Choose IDP Forge When:

• You need multi-model routing to improve accuracy across different document types or pipeline stages.
• BYOK matters because you want to keep billing, data agreements, and governance in-house.
• You process high volumes of complex documents in mortgage, insurance, financial services, logistics, or engineering.
• You need to prove accuracy with ground-truth evaluation before going into production.
• Analyst recognition, patents, and enterprise compliance credentials such as SOC 2 and GDPR matter for procurement approval.

Choose Reducto When:

• You want a fast, visual pipeline-building experience with live previews and one-click deployment.
• Multi-region SaaS deployment in the US and EU is a strict requirement.
• You do not need multi-model routing or BYOK, and a single managed pipeline is acceptable.
• You are part of a smaller or fast-moving team that prioritises speed of adoption over long-term model flexibility.

Choose LandingAI When:

• Your extraction requirements are straightforward and are unlikely to become more complex.
• You do not need workflow completion through an Edit API, continuous learning, or predeployment evaluation tools.
• A single proprietary model is an acceptable trade-off for simplicity.

Conclusion

All three platforms meet the basic requirement of turning documents into structured data with confidence scores and traceability.

The main differences are in control and depth: control over which model handles each task, control over billing and data terms through BYOK, and the depth of tooling available for evaluation, workflow completion, and continuous learning.

Reducto narrows the gap with IDP Forge through its regional deployment coverage and visual pipeline-building experience, but it does not offer multi-model routing or BYOK.

LandingAI is the most limited of the three. It provides core confidence scoring and source provenance but does not include automatic page rotation, workflow completion, continuous learning, or predeployment testing.

For teams processing high volumes of complex, high-stakes documents, where one missed field or untraceable extraction can become expensive, IDP Forge’s combination of multi-model flexibility, BYOK, evaluation tooling, and analyst-verified enterprise credibility makes it the harder platform to outgrow.

*Disclaimer: The information presented in this blog is based on publicly available sources and our interpretation of that information at the time of publication. Product features, capabilities, pricing, performance metrics, and other details may change over time. For the most current and accurate figures, specifications, and commercial information, please contact the respective companies directly.