Solutions · Use case
Document Intelligence.
Generative AI, scoped to the problem it solves.
Citation-grounded retrieval and summarisation over heterogeneous document corpora.
Use-case context
You sit on decades of policy documents, contracts, drawings, medical notes, and submission packets that hold answers nobody has time to retrieve. Off-the-shelf RAG hallucinates citations and drops the clauses that matter, so it fails the moment an auditor, regulator, or clinician asks to see the source. We build retrieval pipelines that index your live corpus with chunking shaped to each document type, cite source spans inline, and refuse to answer below a calibrated confidence floor. Outputs land in the reviewer's queue with the source document, span, and confidence band attached. Measured by citation grounding rate (the share of generated sentences that trace to a verifiable source span) and F1 against a labelled holdout your subject-matter experts assemble during discovery. Hallucination rate is a hard ceiling, not a soft target. We do not deploy document intelligence as the system of record. Outputs supplement the reviewer. They never replace the document repository or the human sign-off. In our coverage footprint this lands first across financial services, healthcare, legal: the sectors where the data shapes and evaluation criteria line up cleanly with what this use-case actually measures.
How this shows up across industries
Where document intelligence lands in production engagements.
Financial Services · Generative AI Consulting
See industry →In financial services, the highest-yield generative AI deployments tend to be document-intelligence over policy and compliance corpora and structured-extraction agents over claims, contracts, and statements.
Legal · Generative AI Consulting
See industry →In legal, generative AI has matured fastest in document review, drafting assistance, and clause-by-clause comparison, always with citations back to source.
Energy · Generative AI Consulting
See industry →In energy, generative AI lands earliest in technical document retrieval, regulatory submission drafting, and operational-data summarisation.
Education · Generative AI Consulting
See industry →In education, generative AI is most defensible when applied to curriculum drafting assistance, accessibility tooling, and administrative document automation.
Data shape
PDFs, scanned images requiring OCR, structured policy databases, contract bundles, clinical notes, regulatory submissions, and the metadata that contextualises each.
Delivering services
Where it lands first
Industries where document intelligence applies.
- 01
Financial Services
Generative AI for banks, asset managers, and capital markets. Built to your regulatory posture.
- 02
Healthcare
Tightly-scoped generative AI for clinical operations and document automation. Never direct clinical decisioning.
- 03
Legal
Citation-grounded generative AI for matter management, document review, and drafting workflows.
- 04
Energy
Generative AI for technical document retrieval, regulatory submissions, and operational summarisation.
- 05
Insurance
Generative AI for claims summarisation, underwriting research, and submission-document classification.
- 06
Telco
Generative AI for customer-care deflection, network-incident summarisation, and provisioning workflows.
- 07
Logistics
Generative AI for exception handling, document extraction, and customer-comms across TMS / WMS surfaces.
- 08
Manufacturing
Generative AI for supplier-document extraction, technical-manual retrieval, and quality-incident summarisation.
- 09
Education
Generative AI for curriculum drafting, accessibility tooling, and administrative automation. Under explicit student-data residency.
- 10
Media
Generative AI for editorial research, asset tagging, and personalised distribution. With human-in-the-loop quality gates.
Where we draw the line
We do not deploy document intelligence as the system of record. Outputs supplement the reviewer. They never replace the document repository or the human sign-off.
Talk to us about a document intelligence engagement
A 30-minute call to scope where document intelligence moves the curve against your evaluation criteria.
Book strategy callWhy work with Veso AI on document intelligence
Measured
Evaluation, not opinion
Measured by citation grounding rate (the share of generated sentences that trace to a verifiable source span) and F1 against a labelled holdout your subject-matter experts assemble during discovery. Hallucination rate is a hard ceiling, not a soft target.
Proven
Quality you can measure
In the first two weeks we build a labelled evaluation set with your experts, so quality is measured from day one, not hoped for.
Production
Built to operate
We hand over working software, infrastructure-as-code, and an evaluation harness your team can run and maintain.
Related use-cases
Structured Extraction
Schema-conformant extraction of fields, entities, and tables from messy inputs.
Internal Copilots
Role-shaped copilots over internal knowledge: Confluence, runbooks, policies, code.
Evaluation Harnesses
Continuous, automated evaluation pipelines for production generative-AI systems.
FAQ
Document Intelligence: frequently asked questions
How is success measured for document intelligence engagements?
Measured by citation grounding rate (the share of generated sentences that trace to a verifiable source span) and F1 against a labelled holdout your subject-matter experts assemble during discovery. Hallucination rate is a hard ceiling, not a soft target. The evaluation harness is part of the deliverable, not an afterthought. We build it during the engagement so your team can run it against the next prompt, model, or pipeline change without us.
Where does Veso AI NOT apply document intelligence?
We do not deploy document intelligence as the system of record. Outputs supplement the reviewer. They never replace the document repository or the human sign-off. This is a deliberate trust boundary, not a capability gap. We are equipped to build the systems we decline to build, and we decline to build them because the risk-to-value ratio in those surfaces does not justify it.
Which industries does document intelligence apply to?
In our coverage footprint, document intelligence most commonly lands in financial services, healthcare, legal, energy. The specific deployment shape varies by industry: data shapes, evaluation criteria, and regulators differ enough that we re-scope each engagement against the sector it lands in.
What data shape do you need to start a document intelligence engagement?
PDFs, scanned images requiring OCR, structured policy databases, contract bundles, clinical notes, regulatory submissions, and the metadata that contextualises each. In the first two weeks we look at the real data (what exists, what is labelled, where it has to live) and build the plan around what is actually there, not around an assumption.
Which Veso AI services ship document intelligence?
document intelligence ships under our Generative AI Consulting, Custom Software Development, AI Integration Services service lines, depending on the integration surface and the build-vs-platform trade-off. Most engagements draw on more than one. The boundary between consulting, custom build, and integration is a scoping decision we make explicit during discovery.
How does a document intelligence engagement typically start?
We spend two weeks with your leadership and operators, build an evaluation set with your subject-matter experts, and come back with a clear plan and a clear price. That evaluation set anchors every decision after it (model choice, prompt strategy, retrieval design) so quality is measurable from week one, not from go-live.
Industries where document intelligence applies
- Financial Services Generative AI for banks, asset managers, and capital markets. Built to your regulatory posture.
- Healthcare Tightly-scoped generative AI for clinical operations and document automation. Never direct clinical decisioning.
- Legal Citation-grounded generative AI for matter management, document review, and drafting workflows.
- Energy Generative AI for technical document retrieval, regulatory submissions, and operational summarisation.
- Insurance Generative AI for claims summarisation, underwriting research, and submission-document classification.
- Telco Generative AI for customer-care deflection, network-incident summarisation, and provisioning workflows.
- Logistics Generative AI for exception handling, document extraction, and customer-comms across TMS / WMS surfaces.
- Manufacturing Generative AI for supplier-document extraction, technical-manual retrieval, and quality-incident summarisation.
- Education Generative AI for curriculum drafting, accessibility tooling, and administrative automation. Under explicit student-data residency.
- Media Generative AI for editorial research, asset tagging, and personalised distribution. With human-in-the-loop quality gates.
Service lines that ship document intelligence