Product family
Product conceptDocument Intelligence
From documents to structured, validated data your systems can trust.
A pipeline that reads incoming documents, classifies them, extracts fields with confidence scores, validates them against business rules and routes uncertain cases to people.
Product concept. This is not a self-serve product yet. There is no public account, live dashboard or price list; we deliver it as a configured build and will show you the architecture, not a staged demo.
/ 01Overview
What it is and why it matters
Back-office teams still re-key data from invoices, claims, onboarding packs and contracts. Optical character recognition helps with text, but the hard part is understanding layout, context and exceptions. Modern multimodal models handle much of that, as long as the surrounding process is engineered for errors.
The Document Intelligence concept combines layout-aware extraction with explicit validation. Each extracted field carries a confidence score and the location it came from. Business rules check totals, dates, identifiers and cross-document consistency. Anything below threshold or failing a rule goes to a review queue where a person confirms with the source highlighted.
We deliver it as a configured pipeline for your document types. The first step is always a labelled sample, because accuracy claims mean nothing without your documents behind them.
/ 02Features
How it works
01
Layout-aware extraction
Tables, key-value pairs, signatures and handwriting regions are handled with models chosen for your document mix.
02
Field-level confidence
Every value has a confidence score and a bounding box, so reviewers jump straight to the evidence.
03
Validation rules
Arithmetic, format, reference-data and cross-field checks catch errors that a model alone would not.
04
Review queue
A focused interface for exceptions, with keyboard-first correction and corrections captured for evaluation.
05
Output to your systems
Validated records are posted to ERP, case management or a data warehouse through APIs or files.
06
Accuracy reporting
Straight-through rate, field accuracy and review effort are tracked per document type over time.
/ 03Actual capabilities vs roadmap
What a first release includes, and what it does not
In scope for a first build
- Classification and splitting of multi-document files
- Field extraction with confidence and provenance
- Rule-based validation and exception routing
- Human review interface
- Export via API, webhook or file
Roadmap, not yet delivered
- Clause comparison against contract playbooks
- Active-learning loop from reviewer corrections
- Template-free onboarding of new document types
/ 04Use cases
Where it earns its keep
Accounts payable
Invoices are captured, matched to purchase orders and posted, with mismatches routed to the AP team.
Customer onboarding
Identity and company documents are checked for completeness and consistency before a case moves forward.
Contract review support
Key terms such as renewal dates, liability caps and governing law are extracted into a register for legal review.
Related solutions: Document & Back-office AI, Finance & Compliance, HR & People Operations
/ 05Integrations
Connects to the systems you already run
Listed systems are integration targets reached through their documented APIs. Their mention does not imply a partnership or endorsement.
Intake
- Shared mailboxes
- SFTP and cloud storage
- Scanning workflows
- Upload portals
Systems of record
- SAP, Oracle, NetSuite, Dynamics
- Case management platforms
- Data warehouses
/ 06Security and governance
Designed for oversight
- Documents can be processed entirely inside your cloud environment.
- Personal data fields can be masked in logs and review screens by role.
- Retention of source images and extracted data follows your policy, with deletion jobs logged.
/ 07Demo
No live product demo yet
There is no live demo of Document Intelligence because it is not a released product. Our demo lab includes a browser simulation on synthetic data that shows one of the core patterns behind it: “Document extraction with validation”.
/ 08Pricing or quote
Priced to your scope, never invented
Priced per engagement, with running costs modelled per document from your volume and page counts.
/ 09FAQ
Questions about Document Intelligence
What accuracy should we expect?
It depends on document quality and variety. We measure it on your own labelled sample during discovery and agree target thresholds before build, rather than quoting a generic figure.
Does every document still need a person to check it?
No. Documents that pass validation above an agreed confidence threshold can flow straight through; the rest go to review. The threshold is a business decision we help you set from measured error rates.
Can it handle scanned and handwritten documents?
Often yes, with lower accuracy than clean digital files. Handwriting-heavy forms are assessed on samples before we commit to automation targets.
Related services
- Service / buildCustom AI SaaS & Multimodal AppsAI-native products and internal applications that work with text, documents, images and audio.
- Service / integrateData Engineering & AI PipelinesThe data foundations AI needs: reliable pipelines, clean models, governed access and lineage.
- Service / integrateAI Workflow & CRM/ERP IntegrationBring AI into the CRM, ERP and service platforms where work already happens.
Explore Document Intelligence with our team
A 45-minute conversation with an engineer: your workflow, the architecture, the risks and what a first version would include.