Solutions · Use case
Document Intelligence.
Generative AI, scoped to the shape of the problem it solves.
Citation-grounded retrieval and summarisation over heterogeneous document corpora.
Use-case context
Operators sit on decades of policy documents, contracts, technical drawings, medical notes, and submission packets that hold answers nobody has time to retrieve. Off-the-shelf RAG products hallucinate citations and collapse the clauses that matter, which makes them inadmissible the moment an auditor, regulator, or clinician asks "show me the source". We build retrieval pipelines that index the live document corpus with chunking shaped to the document type, generate answers that cite source spans inline, and refuse to answer when retrieval confidence falls below a calibrated floor. Outputs land in the reviewer's queue with the source document, the span, and a confidence band attached. Measured by citation grounding rate (the proportion of generated sentences that trace to a verifiable source span) and F1 against a labelled holdout of question-answer pairs assembled by your subject-matter experts during discovery. Hallucination rate is tracked as a hard ceiling, not a soft target. We do not deploy document-intelligence systems as the system of record — outputs supplement the reviewer, they do not 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 that include document intelligence in their applicable use-cases.
- 01
Financial Services
Generative AI for banks, asset managers, and capital markets — under explicit 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 automation 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 systems as the system of record — outputs supplement the reviewer, they do not 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 actually 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 proportion of generated sentences that trace to a verifiable source span) and F1 against a labelled holdout of question-answer pairs assembled by your subject-matter experts during discovery. Hallucination rate is tracked as a hard ceiling, not a soft target.
Fixed-fee
After paid discovery
Two-week discovery assembles the labelled evaluation set with your subject-matter experts, then converts into a fixed-fee proposal with explicit gates.
Your repo
Your IP, day one
Code, infrastructure-as-code, evaluation harness, and runbooks land in your accounts — no vendor lock-in on the data, models, or evaluation history.
Related use-cases
Structured Extraction
Schema-conformant extraction of fields, entities, and tables from messy inputs.
Internal Copilots
Role-shaped copilots over internal knowledge corpora — 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 proportion of generated sentences that trace to a verifiable source span) and F1 against a labelled holdout of question-answer pairs assembled by your subject-matter experts during discovery. Hallucination rate is tracked as 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 systems as the system of record — outputs supplement the reviewer, they do not 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. During the paid two-week discovery we map the actual data surface — what exists, what is labelled, what residency posture it carries — and the proposal for the next gate is shaped against that, not against 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?
With a paid two-week discovery: workshops with leadership and operators, an evaluation-set assembled with your subject-matter experts, and a fixed-fee proposal for the next gate. The evaluation set anchors every subsequent decision — 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 — under explicit 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 automation 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