Spread across formats.
PDFs, spreadsheets, emails and exports each hold part of the picture.
From piles of paper
to records you can use.
Extract, classify, structure, summarize, translate and search, so every document, call and message becomes data you can rely on.
Wherever the work is.
Hosted
Private cloud
On-premise
Edge
Air-gapped
The facts exist.
They just don't connect.
The renewal date is in an email, the notice period is in a contract, the owner is in a spreadsheet. Every answer means opening all three, and hoping nothing was missed.
Inconsistent shapes.
Every supplier, carrier and system writes the same fact a different way.
Answers without sources.
Search and chat tools return confident text with nothing to check it against.
What the AI
can understand.
Structure first.
Language last.
Most understanding is parsing, matching and checking, which rules and small models do well. A language model is used only where it adds something, and never without a source.
Everything sensedSense
Pages, transcripts, frames and feeds.
Parse & normaliseRules & code
Dates, units, names and references made consistent.
Extract & linkSpecialized model
Fields pulled out and linked into one record.
SearchSpecialized model
Relevant passages found and ranked.
AnswerReasoning
Written only from what was found, with citations.
Give notice by 2 July.
Three sources.
Question · Northline Haulage notice date. An answer you can check in a minute, not one you have to trust.
Found. Renewal on the same terms from 30 September.
Found. Either party may end the agreement on 90 days' written notice.
Found. Contract owner is J. Patel, procurement.
Worked out. 30 September minus 90 days is 2 July.
Illustrative example. Supplier, contract and dates are fictional.
Built to be
checked.
Understanding is only useful if a person can see where it came from.
-
A source for every fact.
Each value and each answer links back to the page, cell or second it came from.
Documents -
Knows what it doesn't know.
When the sources are silent, the AI says so instead of filling the gap.
How Check works -
Permission-aware.
People only see answers drawn from documents they are allowed to open.
Security & trust
Where it runs.
The AI goes to where the work is, from hosted to air-gapped.
A managed environment.
Start with a hosted service when speed of adoption and managed operations are priorities. Agree data handling, access and service requirements as part of the engagement.
Discuss hostedIn the cloud you use.
Deploy dedicated instances in your AWS, Azure, Google or Oracle account. Align the architecture with your cloud standards, operational responsibilities and integration requirements.
Discuss public cloudWithin your enterprise network.
Run it inside your own private cloud or VPC, with network access, storage and controls set around your boundary.
Discuss private cloudOn your infrastructure.
Run software, storage and local inference on your own servers. Plan capacity, integration, maintenance and support around the environment your team operates.
Discuss on-premiseClose to the operation.
Place intelligence near industrial sites and operational equipment, where latency and connectivity shape the design. Match the workload to the local compute available.
Discuss edgeWithout constant connectivity.
Operate local workflows without a continuous internet connection. Define how data is transferred, how updates are applied, and what must remain available offline.
Discuss offlineA physically isolated environment.
Plan for an installation with no external network connection. Local models, dependencies, data transfer and maintenance all become part of the deployment design.
Discuss air-gappedThe other capabilities.
Each one is tested on your own work before you rely on it.
Sense
It sees, hears and reads the work as it happens.
Explore Sense →Check
Every line compared. Only the gaps reach you.
Explore Check →Investigate
Follow the evidence across systems. Find out what happened, and why.
Explore Investigate →Anticipate
Know what comes next, and plan for it.
Explore Anticipate →Operate
The next step, taken. The reason, recorded.
Explore Operate →Bring us the work where wrong is expensive.
Start with the operational problem. We’ll work out the data, models and agents it needs, and where it should run.
Talk to us →LondonDiscovery AI Limited · United Kingdom
HyderabadReDscvry Technology Private Limited · India
ChennaiReDscvry Technology Private Limited · India