Bralak AI

Healthcare

Reduce the Administrative Load Around Care.

AI for documentation, scheduling, patient communication and insurance workflows — built for environments where accuracy and privacy are not negotiable.

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A patient request, from arrival to resolution

  1. 01Arrival
  2. 02Identify and triage
  3. 03Retrieve
  4. 04Act
  5. 05Confirm
  6. 06Escalate

Challenges

What slows Healthcare teams down

  • Administrative work competing with clinical time
  • Phone lines that cannot be answered during clinic hours
  • Documentation backlogs
  • Insurance and prior-authorisation processing
  • Information spread across systems that do not talk

The workflow

A patient request, from arrival to resolution

The administrative path only. It is built to end in one of two places: a booked appointment, or a clinician holding a case with the context already assembled.

StageWhat happensSystemsWho decides
01ArrivalA call, a portal message or a form arrives, frequently outside clinic hours.Telephony, patient portal, shared inboxSystem
02Identify and triageThe caller is identified against the record and the request is classified as administrative or clinical. Clinical wording leaves this path immediately.EHR/EMR, scheduling platformSystem, under a clinical keyword floor
03RetrieveEligibility, existing appointments, referral status and the practice’s own policy — scoped to what this requester is entitled to see.EHR/EMR, insurance portal, policy storeSystem
04ActBook, reschedule, or assemble the prior-authorisation packet. Nothing clinical is written.Scheduling platform, document storeSystem, inside booking rules you set
05ConfirmConfirmation on the channel the patient used, stating plainly what was changed.Secure messaging, SMS, emailSystem
06EscalateAnything clinical, anything outside policy, and anything the patient asks to escalate — routed with the transcript, the retrieved context and the reason attached.Practice queue, on-call routingClinician or practice staff

Limits

Where errors cost, and where we would not automate

Both halves of this section are reasons to build less than the maximum. They are here because a supplier who has not thought about them has not built one of these before.

Where an error costs

  • A wrong appointment slot is an inconvenience. A wrong answer about a medication, a symptom or a result is not — which is why the clinical and administrative paths separate at triage rather than at the answer.
  • A prior-authorisation packet assembled with a missing document is rejected weeks later, by which time the delay has already reached the patient. Extraction confidence is surfaced at assembly, not discovered at rejection.
  • A record surfaced to the wrong caller is a disclosure, not a defect. Identification happens before retrieval, and retrieval is scoped to the identified patient.

Where we would not put AI here

  • Triage, diagnosis, dosage and results interpretation — anything a clinician is licensed for. The system routes these; it does not answer them.
  • Autonomous writes to the clinical record. Scheduling and administrative fields, yes. Clinical documentation is drafted for review and signed by a person.
  • Any statement about coverage or cost beyond what the payer’s response actually says. Where that response is ambiguous, the case escalates rather than being interpreted.

Agents

The agents that do this work

Expand any card for the problem it solves, what it does, what it connects to and where a person stays in the loop.

  • Voice Agent

    Answers and places calls, completing real tasks in conversation.

    What it does
    Problem
    Calls arrive when nobody is free, and the work stops while someone answers the phone.
    Actions
    • Answers inbound calls
    • Places outbound calls
    • Verifies callers
    • Retrieves live account data
    • Books and reschedules
    • Updates the CRM
    • Transfers with a spoken summary
    • Files a transcript and summary
    Integrations
    Twilio · SIP · Salesforce · HubSpot · Scheduling platforms · Calendars
    Outcome
    Calls are handled immediately, and the ones that need a person arrive with context.
    How we build this

  • Document Agent

    Extracts, validates and processes business documents.

    What it does
    Problem
    Documents arrive in every format and someone retypes them into a system.
    Actions
    • Classifies document type
    • Extracts structured fields
    • Validates against systems of record
    • Flags discrepancies with both sources
    • Files and posts
    • Requests what is missing
    Integrations
    Email · SFTP · S3 · SharePoint · Accounting systems · ERP · Document stores
    Outcome
    Intake stops being manual, and exceptions surface with a diagnosis attached.
    How we build this

  • Knowledge Agent

    Answers questions from organisational documentation, with citations.

    What it does
    Problem
    The answer exists — in a document, a thread or one person’s memory — and finding it takes longer than the task it unblocks.
    Actions
    • Answers from internal documentation
    • Applies the asker’s permissions
    • Cites sources
    • Says so when the answer is not documented
    • Logs unanswered questions
    Integrations
    SharePoint · Google Drive · Confluence · Notion · Internal wikis · Slack · Teams
    Outcome
    Institutional knowledge becomes reachable, and the gaps become visible.
    How we build this

  • Customer Support Agent

    Handles repetitive support conversations and escalates the rest with context.

    What it does
    Problem
    A large share of tickets are the same handful of questions, and they sit in the same queue as the cases that genuinely need a specialist.
    Actions
    • Answers from documentation and policy
    • Retrieves account and order history
    • Performs account actions within policy
    • Escalates with a written summary
    • Tags and routes
    • Identifies documentation gaps
    Integrations
    Zendesk · Intercom · Freshdesk · Salesforce Service Cloud · Slack · Email
    Outcome
    Routine cases resolve without a queue; specialists receive pre-researched tickets.
    How we build this

Integrations

The systems this connects to

  • EHR/EMR systems
  • Scheduling platforms
  • Twilio
  • Document stores
  • Secure messaging

Selected work

Results, once they are checkable

Selected work is being prepared for publication.

We publish results only once they can be independently verified.

FAQ

Healthcare questions we are asked

Where is patient data processed, and who can see it?

That is decided in the architecture phase and written down before any data moves. Where a hosted model provider is unacceptable, open models are deployed inside your environment instead. Retrieval is permission-aware, so the system can only surface what the requesting context is already entitled to see.

What will the system never do without a clinician?

Anything clinical. The routing logic treats administrative requests and clinical concerns as different paths, and the clinical path terminates in a person every time. That is a designed step, not a fallback — the diagram on this page ends in escalation for exactly this reason.

Can this work with the EHR we already run?

Integration is scoped against the API or interface your system actually exposes, which is assessed during discovery rather than assumed. Where an EHR has no usable API, the workflow is designed around the surfaces it does offer instead of around a replacement project.

How is clinician review built into the workflow?

Approval gates are configurable per action and default to on for anything irreversible or clinical. A reviewer sees the request, the retrieved context and the proposed action together, so the review is a decision rather than a re-investigation.

What audit trail do we get?

Every run records its inputs, the context it retrieved, the reasoning step, the action taken and who approved it. That record is the artefact you show an auditor, and it is written whether or not anyone asks for it.

Solutions

How we build it

Your Next Intelligent System Starts Here.

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