# Which public records management systems offer OCR and automated document classification?

I've been researching the public records management category for a records modernization project, and I noticed G2's own category guidance now answers this exact question directly, so I checked its recommendations against what the review record and product materials actually support. So, which public records management systems offer OCR and automated document classification? Here's what held up:

Everlaw: The strongest current review evidence for the classification half: recent reviews describe AI-driven suggestive coding with accuracy that reviewers say has visibly improved, AI grouping used to build consistent review assignments, and processing that makes uploading large data sets nearly painless, which is what automated classification looks like when working teams describe it. G2's guidance credits it with document processing and AI-powered classification including predictive coding. The recent honest notes: search and homepage organization confuse newcomers, and the platform's habits assume legal-review workflows.
Relativity: The scale machinery: G2's guidance names email threading, near-duplicate identification, and active learning as its classification core with an analytics layer built for OCR-dependent workloads, and recent reviews confirm the analytical breadth across investigations and regulatory requests while flagging the costs, multi-step processes at volume, inconsistent workspace performance, and a real dependence on trained specialists.
NewgenONE: The one with OCR in its actual lineage: enterprise content management roots with native OCR, intelligent classification, and rule-based routing (per G2's guidance and its own materials). The honest caveat I'd attach: its reviewer base is banking and financial services with no visible government records voice, so its public-records fit is a configuration case your references would have to make.
JustFOIA: The FOIA-shaped version of the same outcome: G2's guidance points to its PST extractor, keyword searching across email archives instead of reading each message, which is classification's practical result applied to the record type that makes up agencies' highest volumes. Its recent reviews, all from government administrators, credit ease and time savings rather than naming these features, so the demo carries the proof.

One honest observation from reading everything: the acronym OCR barely appears in this category's review text at all, because working users describe outcomes, searchable scans, suggested codes, grouped documents, not engines. So in demos, skip the checkbox question and bring a box of your worst records, a scanned 1998 fax, a 40,000-message PST, a handwritten form, and ask each vendor to make them searchable and sorted live. The products above will separate quickly. Records folks, what share of your incoming requests still involves scanned paper, and which system actually handled it without manual retyping? That number would ground this whole comparison.

##### Post Metadata - Posted at: about 2 months ago - Net upvotes: 1 ## Comments ### Comment 1 <p>A large share of older records still arrives as scanned PDFs, especially for historical requests, permits, and archived correspondence. The biggest time saver is reliable OCR that makes poor-quality scans searchable, but handwritten forms and faded documents still tend to need manual review.</p> ##### Comment Metadata - Posted at: about 2 months ago - Author title: Marketer ## Related discussions - [How well does Trello scale into a larger team?](https://www.g2.com/discussions/1-how-well-does-trello-scale-into-a-larger-team) - Posted at: over 13 years ago - Comments: 6 - [Can we please add a new section](https://www.g2.com/discussions/2-can-we-please-add-a-new-section) - Posted at: over 13 years ago - Comments: 0 - [Quantifiable benefits from implementing your CRM](https://www.g2.com/discussions/quantifiable-benefits-from-implementing-your-crm) - Posted at: over 13 years ago - Comments: 4