AI
Documents are not merely read; they are understood, checked and routed according to type.
Salytiq combines classification, type-specific extraction, rules and review reasons into a controlled document decision.
Salytiq combines classification, type-specific extraction, rules and review reasons into a controlled document decision.
From intake to outcome
- 01Define document types and unknown cases
- 02Recognise patterns and relevant fields
- 03Apply type-specific checks and confidence
- 04Route structured output or human review
Business outcomes
- Less manual document triage
- No fabricated extraction for unknown types
- Clear reasons for human review
Typical deliverables
- Classification and type model
- Type-specific extractors and checks
- Confidence and review rules
- Test corpus, routing and structured output
When the solution fits
- Multiple document types arrive through one channel
- OCR results need business interpretation
- Unknown documents must safely reach review
Scope boundaries and prerequisites
Clear boundaries
- Unknown or weak documents do not produce fabricated fields
- AI or pattern recognition requires business review rules
Required foundations
- Representative examples for every supported type
- Field definitions, validation rules and review owners
Interactive proof
Open interactive demoDocument Intelligence
Four classifications including an unknown document.
How an engagement can work
- 01
01 Understand
Capture the workflow, effort, systems and visible pain.
- 02
02 Prioritise
Align impact, feasibility and economic value.
- 03
03 Implement
Build, test and clearly hand over one bounded workflow.
- 04
04 Operate
Monitor and improve within an agreed scope.
Frequently asked questions
What does Document Intelligence include?
Salytiq combines classification, type-specific extraction, rules and review reasons into a controlled document decision. Typical deliverables include: Classification and type model; Type-specific extractors and checks; Confidence and review rules; Test corpus, routing and structured output.
What information is needed to get started?
A robust initial scope requires: Representative examples for every supported type; Field definitions, validation rules and review owners.
When is this solution a good fit?
A useful starting point is especially likely when: Multiple document types arrive through one channel; OCR results need business interpretation; Unknown documents must safely reach review.
Which boundaries are clarified before implementation?
Transparent scope boundaries are part of the work: Unknown or weak documents do not produce fabricated fields; AI or pattern recognition requires business review rules.
How can an engagement begin?
We first understand the workflow and prioritise one clearly bounded step. Where the starting point remains unclear, an Automation Audit can prepare the right implementation.
Related solutions
Salytiq
Discuss a projectDoes this solution fit your workflow?
Share the starting point, systems involved and frequency. Salytiq will frame a realistic next step.