Sampled, not checked.
There is time to check a fraction of the lines, so most go through on trust.
Every line compared.
Only the gaps reach you.
Compare, reconcile, match, validate, detect and redact: every record checked against the rules, the contract and every other source, with the evidence attached.
Wherever the work is.
Hosted
Private cloud
On-premise
Edge
Air-gapped
Checking everything
is nobody's job.
Records are compared on a sample, rules are applied from memory, and sensitive details are removed by hand, when anyone remembers. The mistakes live in the part nobody checked.
Rules held in heads.
Tolerances, limits and contract terms are applied however each reviewer remembers them.
Verdicts without reasons.
A flag that says 'mismatch' without showing why is ignored as often as it's acted on.
What the AI
can check.
Rules first.
Judgement where it's needed.
Most checks are exact: a total, a rate, a date, a match. Those run as rules, which are cheap and never drift. Models are used only for the fuzzy parts, like matching names that are written differently.
Every recordUnderstand
Every line from every source, not a sample.
Exact rulesRules & code
Totals, rates, dates, tolerances and limits.
Fuzzy matchingSpecialized model
Names, references and descriptions written differently.
PatternsPrediction
Duplicates and outliers across all records.
To a personOperate
Only breaks, with the evidence attached.
£4,500 left the bank.
Nothing explains it.
Bank reconciliation · cash account 1200 · week 27. Found and explained, not decided. The controller decides what happens next.
Bank. £4,500.00 paid out on 5 July, reference 7731.
Ledger. No entry for £4,500.00 in week 27, or within 10 days either side.
Searched. No open purchase order or invoice for this amount or reference.
Also found. Fuel payment is £54.00 higher in the bank than in the ledger.
Illustrative example. Accounts, payees and amounts are fictional.
Built for
audit.
A check that can't be explained isn't a control.
-
Every verdict has its reasons.
Each pass and fail shows the rule, the values and the sources behind it.
Invoice Errors -
Your rules, versioned.
Rules and tolerances are yours, and every result records which version it used.
Security & trust -
People decide.
The AI checks and explains. People approve, override and sign.
How Operate works
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 →Understand
From piles of paper to records you can use.
Explore Understand →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