Clinical documentation assistant
Ambient and template-based drafting of notes and discharge summaries that clinicians review and sign.
Healthcare & Life Sciences
AI for hospitals, insurers, diagnostics and pharma.
We help healthcare organisations give clinicians time back, speed up claims and understand patient journeys, with privacy, safety and clinical oversight built into every system.
Notes drafted0
Claims coded0%
Clinician time--
The challenge
What is holding healthcare organisations back.
01
Clinicians buried in paperwork
Hours every shift go into notes, summaries and forms instead of patients.
02
Slow, error-prone claims
Manual coding and missing documents lead to denials, delays and cash-flow gaps.
03
Fragmented patient data
HIS, LIS, PACS and billing systems rarely talk to each other, so the patient journey is invisible.
04
Privacy and safety are non-negotiable
Health data is sensitive, and any AI that touches care must be safe, supervised and explainable.
Where AI pays off
Use cases we build and run.
Each one is scoped to a measurable business outcome and shipped to production, not left as a proof of concept.
Medical coding and claims
Suggested ICD and procedure codes with evidence, plus pre-submission checks that catch likely denials.
Patient journey analytics
A single view of referrals, admissions, tests and follow-ups to find leakage and bottlenecks.
Capacity and no-show prediction
Forecasts for beds, OT slots and appointments with targeted reminders for high-risk no-shows.
Medical knowledge copilot
Grounded answers from your protocols, formularies and SOPs with citations for every response.
Pharma and trial analytics
Site selection, patient-finding and pharmacovigilance signal detection from structured and unstructured data.
Our approach
How we deliver in Healthcare & Life Sciences.
The same disciplined loop we use everywhere, adapted to the data, risks and rhythms of your industry.
Built responsibly
- DPDP Act, 2023 and sensitive health data handling
- ABDM and NDHM data standards
- HIPAA and GDPR for global clients
- Clinical safety review and human sign-off
- De-identification and role-based access
Typical stack
01
Weeks 1 to 2
Clinical and operational discovery
We shadow the people who will use the system before designing anything.
- Workflow walkthroughs with clinicians, coders and ops teams
- Data inventory with de-identification and access review
- Use cases ranked on time saved, revenue and clinical risk
02
Weeks 2 to 3
Safety-first design
Humans stay in the loop wherever care is affected.
- Architecture inside your environment, no data leaving without approval
- Clinical safety and evaluation criteria agreed with medical leads
- Integration plan with HIS and EHR vendors
03
Weeks 3 to 8
Build with clinicians
Clinical champions test every release before it reaches the floor.
- Evaluation sets built from real, de-identified cases
- Pilots in one department with daily feedback loops
- Accuracy and hallucination tracking on every output
04
Ongoing
Scale across sites
Rollout follows evidence, one department at a time.
- Monitoring for accuracy, drift and usage
- Training for clinicians and super-users
- Governance committee reporting
Case studies
Results from the field.
Case study 01
Multi-specialty hospital group
Giving doctors two hours back each day
The challenge
Doctors spent a large part of each shift writing discharge summaries and progress notes, delaying discharges and frustrating patients.
What we did
We deployed a documentation assistant that drafts summaries from the chart and dictation, which doctors edit and sign inside the existing HIS.
Results
2 hrssaved per doctor per day
35%faster discharge process
94%of drafts accepted with minor edits
Case study 02
Health insurer (TPA)
Faster, cleaner claims adjudication
The challenge
Claims arrived as scanned bundles, and adjudicators manually matched bills, reports and policy terms.
What we did
A document agent now classifies and extracts every page, checks coverage rules and presents adjudicators with a pre-filled decision and evidence.
Results
60%reduction in handling time
28%fewer avoidable denials
Case study 03
Diagnostics chain
Predicting demand to cut wait times
The challenge
Collection centres were overstaffed on quiet days and overwhelmed on busy ones.
What we did
We built location-level demand forecasts and a staffing planner, plus reminders for patients likely to miss home collections.
Results
19%fewer missed appointments
25%shorter peak-hour wait times
Case studies illustrate the kind of engagements we run. Details are generalised and figures are indicative, not guarantees of results.
Other industries
Explore more of our work.
Financial Services
Credit risk, fraud detection, KYC automation and AI-assisted operations.
Retail & D2C
Demand forecasting, personalisation, pricing and catalogue intelligence.
Manufacturing & Supply Chain
Predictive maintenance, quality inspection and inventory optimisation.
SaaS & Technology
AI features inside your product, usage analytics and support automation.
HR & Talent
Screening, matching, workforce planning and people analytics at scale.
Let's talk about Healthcare & Life Sciences.
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