Migration first.
Most tools want your data moved before they can help, and the project dies there.
Plug it into
the systems you run.
No migration first, and old systems included. You decide what it can read and write in each one, and every call is logged.
Wherever the work is.
Hosted
Private cloud
On-premise
Edge
Air-gapped
The APIs we build.
Call our models and solutions from your own systems, with the permissions for each one written down.
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Model APIs
Call our model families from your own systems. Every output comes back with its source.
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Your model, served
The models we train for you, served through the same API and run on your own servers.
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Solution APIs
Production loss, reconciliation or contract review, built into the systems your teams already use.
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Agent APIs
Hand a task to an agent and get the result back, including where it stopped for a person.
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Data APIs
The data we collect, clean and match for you, served to any system that needs it.
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Events
Your systems get an alert the moment something needs attention, with the evidence attached.
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Custom APIs
We wrap your models, data and workflows in an API your teams and partners can call, wherever it runs.
The work lives in systems nobody will replace.
Most operations run on ERPs, maintenance systems and case tools that are decades old, heavily customised and too important to touch. A new tool that needs them replaced first never gets started.
No modern API.
The system that matters most is often the one with no clean way in.
Another screen to check.
A separate destination is one more place people forget to look.
How the AI connects.
How the AI reaches the systems you already run, and where its findings appear.
Use the best way in each system offers.
A proper API where one exists. Files, reports or screens where it doesn’t. Every connection runs inside your boundary, with its permissions written down.
Every systemSense
Everything the work touches.
APIsRules & code
Where the system offers one.
Files & reportsRules & code
Exports, drops and scheduled reports.
ScreensSpecialized model
Legacy screens read like a person would.
PermissionsOperate
Read and write set per system, logged.
Connected, without
changing a thing.
Every connection leaves a record of what it read, what it wrote and who approved it. Here, a 30-year-old maintenance system, working with the AI.
Migration. None.
Writes. Only planning notes, only after approval.
Owner. Maintenance systems team.
Illustrative example. System, work orders and dates are fictional.
Built to fit in, not take over.
The AI joins your systems; it doesn’t ask them to change.
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Inside your boundary.
Connectors run where the AI runs, including air-gapped sites.
Where it runs -
Written permissions.
Every connection has its read and write rights recorded and enforced.
How Operate works -
Agents use them too.
Agents act only through the connectors you approve.
Agents
Where it runs.
Connectors run where the AI runs, from hosted to air-gapped, inside your boundary.
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-gappedPut them to work.
APIs carry the rest of what we build into your systems. Each is built on the same tested foundations.
Models
Specialist models, evaluated on your data and run inside your boundary.
Explore Models →Agents
Agents that run on their own and hand over to a person at the decisions that matter.
Explore Agents →Products
Ready-made products for recurring jobs, from documents and contracts to sustainability data.
Explore Products →Data
Data collected, extracted and governed, with every value traced to its source.
Explore Data →Evaluations
Tests built from your own cases, rerun every time a model changes, so you always know how well it does your work.
Explore Evaluations →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