AWS Textract Alternative: Document Extraction Without the Developer Tax

AWS Textract is a powerful OCR and document analysis API built for developers who need programmatic text extraction at scale. If you have an engineering team, an existing AWS stack, and the budget to build custom parsing logic on top of raw API output, Textract is a legitimate infrastructure component. Amazon has invested heavily in the underlying ML models, and the API handles high-volume workloads reliably.

But Textract is an API, not a product. It extracts text, forms, and tables as raw JSON, leaving structured business data extraction to you. The gap between Textract’s API response and usable data in your spreadsheet or ERP is an engineering project. You need developers to write parsing logic, map fields, handle errors, build a UI for review, and maintain the pipeline as document formats change. For operations, finance, and AP teams that need data out of documents and into their systems, that gap is the entire problem.

Lido is the strongest AWS Textract alternative for teams that need structured document extraction without building software. Lido’s AI reads any document layout on first upload. No API calls to write, no JSON to parse, no field mapping to maintain. ACS Industries processes 400 purchase orders per week across every vendor format with zero engineering involvement. Soldier Field extracts data from 1,000 vendor invoices per month and was live within 15 minutes of signup.

AWS Textract vs. Lido: a direct comparison

AWS Textract is a document analysis API designed for developers building extraction into custom applications. Lido is a complete extraction product designed for the teams that actually process documents. The comparison comes down to whether you want to build extraction software or use a finished product.

Why teams look for AWS Textract alternatives

AWS Textract is a genuinely capable OCR and document analysis API. Amazon’s investment in the underlying models is real, and for developers building extraction pipelines inside AWS, it is a natural starting point. But the reasons teams look for alternatives all stem from the same root cause: Textract is an API, not a solution.

Textract requires engineering resources to produce usable output. Textract returns raw JSON containing text blocks, bounding boxes, confidence scores, and parent-child relationships. Converting that JSON into “vendor name: Acme Corp, invoice total: $14,832.50” requires custom code. You need developers to write field mapping logic, handle variations across document layouts, build error handling for low-confidence extractions, and maintain the pipeline over time. For every hour your AP team saves on data entry, your engineering team spends hours building and maintaining the extraction layer. That tradeoff only makes sense if you already have dedicated developer resources with spare capacity.

There is no user interface. Textract has no built-in way for a non-technical user to upload a document, review extracted data, correct errors, and export results. If your operations or finance team needs to validate extractions before they flow into your ERP, someone has to build that review interface. The AWS Console shows raw API responses—it is a developer tool, not a document processing workflow. Lido provides a visual interface where teams upload, review, and export without engineering support.

Custom field extraction requires additional engineering. Textract’s Analyze Document API extracts generic forms (key-value pairs) and tables. But extracting specific business fields—like a GST number, a PO reference embedded in a description field, or a custom field unique to your vendor’s invoice format—requires writing Queries, building post-processing logic, or training custom models. G2 reviewers note that “extracting custom fields like GST numbers or bank information requires improvement.” Lido handles custom field extraction natively—you describe the field you want in plain English, and the AI finds it regardless of where it appears on the page.

Complex tables are unreliable. Textract offers table extraction, but users report that “complex tabular data extraction is very complicated” and “complex tables sometimes do not process properly.” Nested tables, merged cells, multi-page tables, and tables without visible grid lines are common in real-world business documents. If your invoices contain multi-page line item tables—and most do at any meaningful volume—Textract’s table extraction will require significant post-processing to produce usable output.

Costs are unpredictable and compound. Textract charges per API call: $0.0015/page for text detection, $0.015/page for forms or tables, and additional charges for Queries. Processing a single invoice through text detection + forms + tables + queries can cost $0.05–$0.10 per page. At 5,000 pages per month, that is $250–$500 in API fees alone—before you account for the engineering time to build and maintain the integration. And every failed extraction costs the same as a successful one. Lido’s pricing is flat and predictable, with free reprocessing when results need refinement.

What AWS Textract users actually say

Textract holds a 4.4/5 on G2 and solid ratings on Gartner Peer Insights. The OCR engine is strong for printed text, and teams already invested in AWS appreciate the ecosystem integration. But the complaints consistently point to the gap between API capability and production readiness.

On accuracy: “Not always precise with complex layouts or industry-specific terms.” “Struggles with accuracy, especially when processing handwritten elements and documents with pencil marks.” “Some formatting or nested tables may not always extract perfectly on the first pass.” The pattern is clear: Textract works well on clean, structured documents but requires “extra cleanup and custom logic to make the output usable” on real-world inputs.

On complexity: “Extracting coordinate functions for tabular structures or CSV formats is difficult.” “Complex tabular data extraction is very complicated.” Users report that getting from Textract’s raw JSON to usable business data requires substantial engineering effort—exactly the overhead that operations and finance teams cannot absorb.

On custom fields: “Standard invoice fields work, but extracting custom fields like GST numbers or bank information requires improvement.” “Does not support Cyrillic characters.” When your documents contain fields that do not map to Textract’s pre-built categories, you are writing custom extraction logic yourself.

On cost: “Cost can become expensive for businesses processing a large volume of documents.” The per-page API pricing looks cheap in isolation, but compounding across multiple API calls per document, plus the engineering hours to build and maintain the pipeline, makes the true cost significantly higher than the listed rates suggest.

To be fair: Textract is a solid infrastructure component for engineering teams building within AWS. The API is well-documented, the models improve with each update (the June 2025 update improved rotated text and low-res fax handling), and for programmatic extraction at scale it delivers. The problems surface when teams without dedicated engineering resources try to use it for business document processing.

What teams achieve after switching to Lido

The results below come from teams that chose a complete extraction product over building on top of an API. The pattern: once you remove the engineering project between the API and usable output, time-to-value drops from weeks to minutes.

ACS Industries (Manufacturing, 1,000+ employees) processes 400 purchase orders per week from vendors who send every format—PDFs, spreadsheets, images, and plain-text emails. Each vendor uses a different layout. With Lido: 30 hours saved per week on manual data entry, 99.5–100% accuracy on typed documents, and they avoided hiring an additional FTE. No API integration. No custom parsing code. No developer involvement.

ACS Industries “Thanks to Lido, we’re processing ~400 weekly POs automatically with complete accuracy.”

Soldier Field / ASM Global (Events, 1,000+ employees) handles 1,000 vendor invoices per month, each in a different format. They tried ChatGPT and Power Automate before switching to Lido. What used to take 20 hours per week now takes 30 seconds per invoice. Setup took 15 minutes—not the weeks of engineering time a Textract integration would require.

Soldier Field / ASM Global “What used to take us 20 hours each week now takes just 30 seconds per invoice.”

Relay (Healthcare, 50–200 employees) processes 16,000+ Medicaid claims every 1–2 months, each running 700+ pages. With Lido: 100+ hours saved per week, 500% increase in team capacity, 98% reduction in human error. A team this size does not have engineering resources to build a Textract pipeline, maintain it, and handle the edge cases that medical claims present. Lido worked out of the box.

Relay “Lido turned a process that used to take weeks or months into just hours.”

Esprigas (Energy, gas distribution) processes 27,000 documents per month. They migrated from Docparser to Nanonets before finding Lido. Each previous tool required configuration per document format—templates for Docparser, model training for Nanonets. Lido’s AI handled every format on first upload without any setup.

Esprigas “We were spending a ton of time retraining the models. With Lido, it just works.”

Pricing: AWS Textract vs. Lido

Textract’s per-page API pricing looks cheap until you calculate the total cost of producing usable output. The API fee is just one line item in a much larger budget.

AWS Textract’s pricing. Pay-per-API-call with no monthly minimum. Text detection: $0.0015/page. Forms extraction: $0.015/page. Tables extraction: $0.015/page. Queries: $0.005/page per query. Expense analysis: $0.01/page. A typical invoice processed through forms + tables + 3 queries costs ~$0.045/page in API fees. Free tier covers limited pages for 3 months only. But the real cost is engineering: building the integration, writing field-mapping logic, creating a review UI, handling errors, and maintaining the pipeline. A mid-level developer spending 2–4 weeks building the initial pipeline costs $5,000–$15,000 in engineering time, before ongoing maintenance.

Lido’s pricing. $29/month for 100 pages and 1 user. $7,000/year for 42,000 pages and up to 10 users. Enterprise pricing from $30,000/year for higher volumes, dedicated support, and custom integrations. Free trial: 50 pages, no credit card required. Month-to-month—no annual commitment required. Zero engineering cost. Zero integration time. Zero maintenance overhead.

The math for mid-volume teams. A team processing 5,000 pages per month through Textract’s forms + tables APIs: ~$150/month in API fees ($1,800/year). Looks cheap. But add 2–4 weeks of initial engineering ($5,000–$15,000), ongoing maintenance (20+ hours/quarter), a review UI that someone has to build and host, and error handling for edge cases. Year-one total cost: $15,000–$25,000 including engineering. That same team on Lido: $7,000/year with zero engineering involvement, a built-in review interface, and free reprocessing.

When AWS Textract might still be the right choice

Textract is a real product solving real problems. Here is when it makes sense to use it or stay with it:

You are building extraction into a custom application. If your engineering team is building a SaaS product, internal tool, or automated pipeline where document extraction is one component, Textract is a strong API to build on. It is infrastructure, and if you need infrastructure, it delivers.

You are already deep in the AWS ecosystem. If your documents live in S3, your processing runs on Lambda, and your data flows through SQS and DynamoDB, Textract integrates natively. Adding Textract to an existing AWS pipeline is straightforward for teams that already manage AWS infrastructure.

You process millions of pages and have engineering capacity. At very high volumes (1M+ pages/month), Textract’s per-page API pricing can be cost-effective—if you already have the engineering team to build and maintain the integration. The volume discount tiers reduce per-page costs significantly at scale.

You need raw OCR output, not structured business data. If your use case is text extraction for search indexing, content digitization, or archival—not field-level data extraction from business documents—Textract’s DetectDocumentText API is fast and affordable at $0.0015/page.

If your need is simpler—get structured data out of invoices, POs, receipts, and other business documents without building software—a product like Lido, Nanonets, or Docsumo is a better fit. For teams evaluating other extraction tools, see our comparisons with ABBYY, Rossum, and Kofax.

How to test Lido against AWS Textract

Step 1: Upload a document you process regularly. Pick an invoice, PO, or receipt from a vendor whose format varies. Upload it to Lido and describe the fields you need extracted. No AWS account, no API key, no code.

Step 2: Compare time-to-first-result. A Textract integration requires setting up IAM roles, writing API calls, parsing JSON responses, and mapping fields to your schema. Lido’s free trial gives you structured, labeled data in under 5 minutes. Run the same document through both and compare accuracy and the total effort required to get usable output.

Step 3: Test with your hardest documents. Upload scanned faxes, handwritten forms, multi-page invoices with complex line item tables. These are the documents that expose the gap between raw API output and production-ready extraction. See whether Lido’s AI handles the complexity without custom code—the exact scenario that requires significant engineering with Textract.