The short version
Cogneris is a multi-document, ReAct-architecture document AI platform with pay-per-page pricing, multi-LLM extraction, and a complete platform stack including review queues and audit trail. Azure Document Intelligence is Microsoft's document extraction service inside Azure — strong primitives and Microsoft 365 integration, with Azure OpenAI for LLM augmentation.
Capability comparison
| Capability | Cogneris | Azure Document Intelligence |
|---|---|---|
| Product type | Complete platform — extraction, validation, workflows, audit trail | Cloud service — extraction APIs you compose into a workflow |
| Pricing model | Pay-per-page, includes review & audit features | Pay-per-page, additional Azure costs for storage / Key Vault / orchestration |
| Pre-built models | 40+ document types out of the box, configurable | Pre-built models for invoices, receipts, ID, W-2, 1040, layout, general forms |
| LLM strategy | Multi-LLM (OpenAI + Anthropic), zero-retention configured | OpenAI integration via Azure OpenAI Service, Microsoft models |
| Workflow / orchestration | Built-in: review queues, validation rules, webhook callbacks | Bring your own — Logic Apps, Functions, or external orchestrator |
| Custom model training | Few-shot config + active learning queue | Custom training in Document Intelligence Studio |
| Audit trail | Immutable per-request log with prompt hash, model version, response | Azure Monitor integration; you design the schema |
| Compliance | SOC 2 Type II in progress, GDPR DPA, CCPA, HIPAA BAA on Enterprise | Inherits Azure's compliance posture (extensive) |
| Vendor lock-in profile | Standard REST API, portable schema | Azure ecosystem; portability requires migration work |
| Best fit | Teams that want a complete platform with batteries included | Teams deep on Azure that want raw building blocks |
When to choose which
Choose Azure Document Intelligence when…
- You're already on Azure and want a service that lives next to your IAM, Key Vault and data.
- You're standardising on Microsoft 365 / Power Platform — Azure DI integrates natively.
- You need Azure's specific compliance certs (FedRAMP, IL5, GovCloud) for federal workloads.
- You have engineers to assemble the platform — review UI, audit schema, orchestration — yourself.
Choose Cogneris when…
- You want a complete platform with review queues, validation rules, audit trail, and orchestration out of the box.
- You need multi-LLM across providers, not just Azure OpenAI.
- You want vendor-portable extraction that doesn't lock you into Azure.
- You need full audit lineage per request (prompt, model version, response) without a custom logging pipeline.
- You're embedding document AI in a product shipped on a different cloud than Azure.
Platform vs primitive
Azure Document Intelligence excels at the extraction primitive — pull structured data from a form or document, with strong accuracy on invoices and US tax forms. It is not a complete platform. Production use requires you to add review queues for low-confidence extractions, validation rules, audit-trail schemas, alerting, and orchestration via Logic Apps or Functions. Cogneris bundles those into the product. Azure DI gives you maximum building-block control if you have a platform team. Cogneris is a faster path to production if you don't.
Azure prebuilt models vs Cogneris pages
As of June 2026, Azure Document Intelligence positions prebuilt models as the fast path for common forms. That is useful when the model matches the document exactly. Cogneris maps the same buyer intent to document-specific pages, schemas, validation rules, review routing, and audit evidence.
| Azure prebuilt model intent | Cogneris target page | When Azure is enough | When workflow/review is needed |
|---|---|---|---|
| Invoice | Invoice extraction API | Single invoice parse into an Azure-native app. | AP approval, PO matching, duplicate checks, GL hints, ERP handoff. |
| Receipt | Receipt extraction API | Expense receipt field capture. | Policy review, duplicate detection, merchant normalization, T&E routing. |
| Bank statement | Bank statement extraction API | Statement text and transaction extraction. | Lending, reconciliation, multi-page stitching, reviewer evidence. |
| ID document | ID card OCR API | Basic identity field extraction. | KYC portals, proof-of-address checks, fraud signals, exception handling. |
| Tax and paystub forms | Tax form extraction / Payroll extraction | Known US tax/payroll forms. | Underwriting packets, income verification, audit-ready reviewer changes. |
| Mortgage documents | Mortgage document extraction | Azure-first loan document parsing. | Loan packets with multiple document types, missing evidence, and review state. |
| Layout and general document | Document parsing API | Raw layout extraction for an internal Azure pipeline. | Schema output, citations, validation, and workflow handoff. |
LLM strategy
Azure DI's LLM story is Azure OpenAI — strong, well-integrated, but single-provider. Cogneris routes to OpenAI direct, Anthropic, or both, configurable per tenant. Customers who want failover between providers, or who have explicit anti-Microsoft provisions in their procurement (some financial-services regulators effectively prefer this), find Cogneris's flexibility easier to reason about. Customers happy on Azure OpenAI get tighter integration from Azure DI.
Compliance & certifications
Azure's compliance footprint is comprehensive — FedRAMP, ISO 27001, SOC 2, HIPAA, IL4/IL5, GovCloud. Cogneris is currently SOC 2 Type II in progress with GDPR DPA, CCPA service-provider framing, and HIPAA BAA on Enterprise. For federal or defense workloads requiring IL5+, Azure DI is the answer. For commercial enterprise workloads, Cogneris's posture is sufficient and broadening.
Switching considerations
If you're evaluating Cogneris against Azure Document Intelligence as your incumbent, the practical pieces matter:
- Schema portability — Cogneris emits clean JSON; if your pipeline already consumes Azure Document Intelligence's output, mapping is typically a one-day translation layer.
- Side-by-side evaluation — we run a 7-day evaluation against your real documents alongside your existing Azure Document Intelligence workflow. You get an accuracy and latency report you can show your CTO.
- No annual commit — start with a month-to-month plan, scale up as confidence builds. The pay-per-page pricing means you only pay for what you actually process.
For the full security and compliance posture, see our trust page. For pricing, see pricing. For a side-by-side evaluation against your current workflow, talk to our team.