Zyposoft
AI with the brakes still on

Let the software do thelooking. You do the deciding.

We build AI that reads what your teams would otherwise have to read, points at what needs attention, and takes over only the small, well-defined jobs you have agreed it can.

Knows the situation · Shows its evidence · A person reviews · Everything logged
How a suggestion is handled — illustrativeIllustrative
Reads the situation
Gathers what matters
Works it out
Suggests something
A person reviews
Acts, if allowed
Written down
One run, start to finish
What it can see
3 sources used
Nothing missing
What it suggests
Suggested next step is ready. Nothing happens until you say so.
Human review
AcceptModifyReject
What it did
ActionHeld
AuditRecording
AIisusefulwhenitunderstandstheworkaroundit.Automationissafewhenyouhavedrawnthelineitcannotcross.Adecisionistrustedwhensomeonecancheckwhatitwasbasedon.Andallofitonlyworksifeveryactionleavesatrail.
Where it actually helps

Too much to read, the same work done twice, and risks nobody spots in time.

Too much to read

Half the job is hunting through systems, documents and message threads before anyone can act.

It does the hunting
The same work, again
You find out too late
It depends who is on shift
Copying between systems
Nobody can explain it later
How it works

What happens between the information and the action.

01
It works out the situation

It picks up only what it is allowed to see — where the work has got to, who is involved, what is attached.

What it looks at
Workflow state
User or role
Relevant records
Missing-data status
02
It gathers what matters

It pulls together what this particular job needs, and shows you what it could not find.

What it found
Included context
Excluded / missing
Data source
Freshness
03
It works something out

Sometimes that is the AI, sometimes it is plain rules, often both together.

What it produced
Advisory / summary
Classification
Confidence
Policy constraints
04
A person checks it

Wherever the stakes or your own rules call for it, someone has to agree before anything moves.

What you can do with it
Accept
Modify
Reject
Escalate
05
It acts, and it is recorded

It does only the thing it was allowed to do, watches what happened, and writes it all down.

What it did, and the record
Action status
Destination
Monitoring
Audit event
What it can do

Five jobs it is genuinely good at.

1

Suggesting the next step

The relevant information and a recommendation, in the screen someone is already working in.

It helps whoever is responsible. It does not become responsible.
Clinical workflow supportOperational guidancePolicy assistanceException reviewDecision preparation
2

Reading the paperwork

Pulling the useful parts out of documents, sorting them, and summarising them for someone to check.

Anything it pulls out still gets checked as carefully as the job demands.
Document classificationStructured extractionReview preparationRecord summarisationInformation routing
3

Deciding what comes first

What is waiting, what is late, and what looks wrong — ranked by rules you agreed.

Queue prioritisationPending-task visibilityEscalation supportException detectionOperational alerts
4

Handling the routine steps

For narrow jobs where you have defined the inputs, the limits and what to do when it goes wrong.

If it cannot be undone, it does not get automated.
RoutingNotificationTask creationStatus updatesApproval workflows
5

Help inside the product

Assistance built into the screens people already use, rather than a chatbot bolted on the side.

Guided workflowsContextual helpReview assistantsSmart formsCommand interfaces
Where people use itHealthcare workflowsEnterprise operationsProduct intelligenceDocument-heavy processesSupport and serviceCompliance-sensitive
Any real use case needs the workflow defined, the data cleared, the output validated and a person overseeing it. The screens above are illustrations, not a live product.
Keeping it in bounds

The limits matter more than the cleverness.

What it may see, what it may do, who signs it off and what gets written down — all decided before it runs, not after.

How a request travels
Someone starts a job
We check who they are
Is the data good enough
Do your rules allow it
The AI does its part
A person reviews
The action happens
All of it is logged
When a person has to sign it offReviewed
It is allowed to lookIt suggests somethingA person edits itThe edit is usedBoth versions kept
When it may act on its ownExecuted
A known triggerRules permit itIt does one narrow thingThe far end confirmsMonitoring agrees
When it should not run at allBlocked
Data missing or too oldRules say noNothing is touchedThe reason is recordedA person picks it up
The controls behind it
It only sees data it is allowed to
It knows who is asking, and their role
It checks the data is complete and current
Your rules decide when it may run
Review is required, not optional
Every output can be traced to its sources
You can tell which version produced what
It can only act inside limits you set
When something breaks, it fails safely
Monitoring, and a way to review incidents
What it plugs into
Zypocare OneZypo Clinical AIIntegration PlatformEnterprise applicationsData platformsDocumentsWorkflow servicesIdentity providersMonitoring & audit
AI and automation outputs remain subject to organisational policy, authorised review requirements and domain-specific validation.
Zyposoft does not position intelligent automation as a replacement for professional accountability.
How to start

Pick one job. Make it small enough to judge.

The projects that work start narrow: one person, one task, one clear line for what it must never do.

01
Say what the job is
How it works todayWhose job it isWhat is painful about itWhat good looks likeWhat it must never do
02
Work out what it needs to see
Which systemsWhat informationWho owns itHow recent it must beWhat to do when it is missing
03
Draw the lines
Who can use itWhen a person must reviewWhat is off limitsWhat happens when it failsWhat gets logged
04
Build the thing
What it producesHow it cites its sourcesWhat it may doHow people interact with itHow it connects
05
Prove it on something small
Experts check itTest the workflowTry to break itOne team, one monthWatch it closely
06
See whether it earned its keep
Is it usefulDo reviewers trust itWhat it got wrongDid the work improveAdjust the rulesThen widen it
What is possible depends on your workflow, the data we are allowed to use, how ready your systems are to connect, and who can validate the output. To be plain about it: we are not promising this deploys quickly, that it is always right, that it runs without people, that it works with everything, or that it will save a specific amount of money or time.
Zyposoft Technologies is a product engineering company based in Bangalore, building software for healthcare and enterprise operations. Our products are Zypocare One, the connected hospital platform; Zypo Clinical AI, which adds intelligence a clinician can overrule; and the Integration Platform that keeps them working with the systems already in place.
Products
Zypocare OneZypo Clinical AIIntegration Platform
Solutions
Healthcare TransformationEnterprise Product EngineeringAI and AutomationCloud, Data and Integration
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Bangalore, IN
#7, Nisarga Layout
Chikkalsandra
Bangalore 560061
India
info@zyposoft.com
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