Industries · Healthcare
Banao builds and ships healthcare AI into live clinical and operational workflows — ambient clinical documentation, patient triage and communication, claims automation, and imaging support — for hospitals, clinic chains, diagnostic labs, and healthtech platforms.
Every system below is built compliance-first, wired into your EMR or HMIS, and designed around the clinician's day. We deliver deployed systems, not pitch-deck demos.
Hummcare— a mental-health platform with AI-driven therapist matching, built and shipped end to end.
Each of these maps to a number a CMO or CFO already tracks — clinician hours, denial rate, no-show rate, read time per scan. We start where the cost is measurable.
Voice-to-EMR capture with LLM summarisation and structured field extraction, so a consult ends with the note already drafted instead of two hours of after-hours typing.
Conversational intake that routes patients to the right specialty and books the appointment, cutting mismatched visits and the walk-ins that belonged in primary care.
WhatsApp and voice agents wired into scheduling and the EMR, handling appointment, results, and follow-up queries in English, Hindi, or Arabic — escalating only complex cases to your front desk.
Document intelligence over claim forms and medical records, a payer-rules engine, and denial management, so turnaround time and AR days stop being a black box.
Custom vision models for specialty imaging, or a workflow and reporting layer over existing imaging-AI vendors, to cut read time per scan and even out inter-reader variability.
Forecasting over bed, OR, and supply data with dashboards the operations team opens daily — bed turnaround, OR utilisation, and supply leakage made visible.
Some clients we can name; others are under confidentiality. Metrics shown dotted (··) are being finalised in our case-study metrics pack — the work is real, and we will not publish a number before it is verified.
Hummcare
Hummcare needed a mental-health platform that paired patients with the right therapist and ran sessions, content, and a provider dashboard in one place. Banao built the web platform, the mobile apps, the therapist dashboard, and the AI-driven matching and content engine end to end.
A GCC healthcare provider
A UAE-based provider was buried under appointment, results, and follow-up queries across phone and chat. Banao is building an AI agent paired with EMR integration and Arabic–English handling that answers routine queries directly and routes only the complex ones to staff — with a compliance layer designed in from the first sprint. The client is named on request under NDA.
Banao runs a ~300-person engineering company on its own AI before any client sees it. InterviewGod screens our own hires. Vikaas runs our own demand generation.
In healthcare that matters more, not less: a vendor that depends on its own systems every day designs for uptime, audit, and adoption — not for a demo. The version that reaches your clinicians has already had to survive ours.
Most vendors will sell you a model regardless. We would rather tell you when not to build — it is why medical directors take our second call.
Healthcare is too risky for a bet-the-farm engagement on day one. We start by proving the cost of the problem and the compliance path, not by quoting a build.
On-site if needed. You walk out with a prioritised list of AI opportunities, a compliance and integration read on each, baseline ROI maths, and a go/no-go per opportunity — yours to keep either way. If you proceed, the Sprint cost is credited against the build.
Compliance and data first, then the model. We design data residency, audit logs, and role-based access up front, and integrate with your EMR, HMIS, or LIS — including the older systems.
Deployment with a clinician in the loop, a dashboard, and change management for the clinical and front-desk teams. The system keeps improving with each week of real use.
Our EMR vendor says we can't integrate. Is this dead on arrival?
Almost never. We've worked against locked EMRs by finding an API, an HL7 feed, or a database read path, and we run an integration audit in week one so you know what's possible before committing budget. Most 'you can't integrate' answers change once there is a contract.
How do you handle compliance — HIPAA, DISHA, UAE PDPL?
Compliance-first, by default: data residency in your jurisdiction, encryption at rest and in transit, audit logs, and role-based access. We've built against HIPAA, NABH, GDPR, UAE PDPL, and Saudi NPHIES considerations, and we'll run a compliance architecture review as part of the first conversation.
Our clinicians won't adopt another tool.
They adopt what makes the day shorter. We design the clinician workflow first and keep the AI out of the way until it saves a step — the note that drafts itself, the query that never reaches the front desk. Change management for the clinical team is a delivery item, not an afterthought.
How do we prove ROI before committing budget?
That is what the AI Discovery Sprint produces — fixed price, two weeks, you keep the ROI model and the compliance read whether or not you continue. Worst case you have a free assessment; best case you have your board business case.
How fast can a system reach clinical use?
A typical path is a 2-week Sprint, a 6–8 week build, and a 4-week rollout with a clinician in the loop. Banao's ~300-engineer bench means delivery starts in weeks, not the months a local hire would take.
Bring your biggest source of clinician overload, claim denials, or missed follow-ups. In 45 minutes we'll map the AI opportunity, the compliance path, and the ROI maths behind it.
Book a 45-min scoping call