super.AI

What is super.AI?

super.AI is an intelligent document processing (IDP) platform that turns invoices, claims, bills of lading and other complex documents into structured data. It combines large language models, computer vision and human-in-the-loop review, so uncertain fields go to a person before data reaches your systems. The homepage says users can build end-to-end workflows by describing them in conversation rather than writing code, and the company offers contractual accuracy SLAs per workflow.

The company began in 2018 under the name Canotic, according to one IDP vendor directory, and was led by founder and CEO Brad Cordova when it announced its Unstructured Data Processing platform in March 2022. Older material placed it in Bellevue, Washington, while a June 2026 press release lists Denver, Colorado, names Ben Kwon as CEO and announces an integration with Bosch FleetME. The site lists Visa, Saint-Gobain, Bureau Veritas, CHI Cargo and Nory as customers. super.AI was live and taking sign-ups in October 2026.

Key Features

• Data extraction: super.AI extracts fields from structured, semi-structured and unstructured documents, including typed, scanned and handwritten pages. It reads digital and scanned PDFs plus TIFF, GIF, JPEG and PNG images, and the company says cursive handwriting is supported.
• Classification and routing: super.AI sorts incoming documents by type and routes each one to the right workflow automatically. The company claims more than 90% classification accuracy, which matters when mixed batches of invoices, contracts and forms arrive together.
• Human-in-the-loop review: super.AI sends low-confidence results to human reviewers before the data is released. This review layer underpins the contractual accuracy SLAs, which the company says typically range from 95% to over 99% depending on document complexity.
• Data Processing Crowd: super.AI offers an on-demand, managed workforce for human review through its Data Processing Crowd service. Teams without spare staff can outsource verification instead of building an internal review desk.
• Redaction: super.AI redacts personal and health information (PII and PHI) from documents before they are shared or stored. Audit trails record what was removed, which helps compliance teams in finance, insurance and healthcare-adjacent work.
• Table recognition: super.AI captures repeating rows from tables, such as invoice line items and cargo manifests. This avoids manual re-keying of long lists, which is often the slowest part of processing purchase orders and bills of lading.
• Email attachment scanning: super.AI watches email inboxes and processes attachments as they arrive. Shared services teams can automate intake from suppliers or customers without asking them to change how they send documents.
• No-code agentic workflows: super.AI builds end-to-end document workflows through a conversational, no-code builder driven by AI agents. Workflows can validate extracted data against ERP systems or databases, and you can choose which OCR or LLM models to use.

Pros

• Accuracy backed by contract: super.AI offers contractual accuracy SLAs per workflow rather than vague accuracy promises. Combining AI with human review gives buyers a measurable quality commitment for documents that feed finance or compliance systems.
• Free way to start: super.AI provides a free Starter tier with 25,000 credits and no credit card required. You can test extraction on your own documents before talking to sales about Growth or Enterprise plans.
• Handles messy documents: super.AI processes handwriting, scanned pages and variable layouts that defeat rule-based OCR templates. G2 reviewers, who rate it 4.6 out of 5 across 12 reviews, praise how it structures unstructured data.
• Published customer results: super.AI cites concrete outcomes from named customers on its site. Bureau Veritas reported a 75% cut in processing time and 80% cost savings, and a 2026 release claims a 92% drop in manual review for a logistics firm.
• Enterprise security basics: super.AI states it is SOC 2 and GDPR compliant, with granular role management and detailed audit logs. These controls help regulated teams in banking and insurance clear procurement reviews faster.

Cons

• Opaque paid pricing: super.AI does not publish prices for its Growth or Enterprise plans. Budgeting requires a usage estimate or a sales call, which slows comparison with IDP tools that list per-page rates.
• Costlier than basic OCR: super.AI can cost more than plain OCR software, as one G2 reviewer pointed out. Teams with simple, consistent forms may not need human review and could pay less elsewhere.
• Niche data takes work: super.AI can be harder to tune for specialised datasets, according to a G2 reviewer working in healthcare. Expect a setup period before accuracy reaches the SLA level on unusual document types.
• Small vendor footprint: super.AI is a relatively small company, which one IDP directory lists at about 40 staff. Large enterprises may question its capacity to support big rollouts compared with vendors that employ hundreds of engineers.
• Inconsistent company details: super.AI’s headquarters and leadership differ across public sources, from Bellevue and San Francisco to Denver. Buyers doing vendor due diligence should confirm the current entity and contacts directly with the company.

Who is Using super.AI?

• Financial services teams: Automate KYC onboarding, loan applications and bank statements.
• Insurers: Extract data from claim forms and supporting documents.
• Logistics and freight firms: Process bills of lading, customs forms and invoices at volume.
• Shared services centres: Handle purchase orders and supplier invoices from email inboxes.

Pricing

super.AI is free to start with 25,000 Starter credits, while Growth and Enterprise prices are not published (super.AI site and llms.txt, checked October 2026).

Third-party directories such as the IDP vendor listing we checked still say pricing is not disclosed, so the free Starter tier is the only figure the company publishes. Request a quote based on your monthly page count before you commit, since usage-based bills depend heavily on document complexity and review depth.

What Makes super.AI Unique?

super.AI sells an accuracy outcome rather than an extraction model. Most IDP tools return AI output with a confidence score and leave the checking to you, whereas super.AI routes doubtful fields to human reviewers, including its own managed crowd, and backs the result with a per-workflow accuracy SLA. Its open architecture lets you swap in different OCR and LLM models, and the conversational workflow builder aims to let operations staff, not just developers, design the whole pipeline from inbox to ERP.

Compatibilities and Integrations

• Business systems: Pre-built connectors for Salesforce, SAP, NetSuite, SharePoint and major document management systems.
• Storage: Amazon S3 connections for document intake and output.
• API: API integrations documented at docs.flows.super.ai, plus ERP and database validation sync.
• Partners: A Bosch FleetME integration announced in June 2026 for industrial document workflows.

super.AI Tutorials

A first super.AI workflow takes a few short steps.

1. Sign up on super.ai for a free Starter account with 25,000 credits.
2. Upload sample documents or connect an email inbox for intake.
3. Describe the fields and rules you need in the conversational workflow builder.
4. Set confidence thresholds so uncertain fields go to human review.
5. Connect the output to your ERP, CRM or storage through a connector or the API.

How We Rated It

Summary

super.AI suits finance, insurance and logistics teams that need near-perfect data from messy documents and want an accuracy commitment, not just a model. Its main limitation is opaque paid pricing, which makes cost comparison with simpler OCR tools difficult. We would start on the free Starter tier with your hardest real documents, then measure how many fields reach human review before asking for a Growth quote.