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Home · Industries · Long-Term Care
Long-Term & Post-Acute Care · Senior Living · Home Health

AI that gives caregivers their time back

Long-term care runs on thin margins, chronic staffing shortages, and a documentation burden that pulls nurses away from residents. We deploy AI across the post-acute and senior-living journey — clinical-record extraction, billing and claims, remote resident monitoring, workforce scheduling, and family communication — built for the privacy and audit demands of HIPAA, the NHS, and DPDP. Every deployment runs inside the operator's perimeter, because resident health data is the last thing you want sitting in a public LLM API.

40%
Documentation time returned to care
30%
Fewer agency-staffing hours
99%
Claims-coding accuracy
Sovereign
On-prem PHI handling
Key Challenges

Where Long-Term Care organisations need AI most

01

Caregiver documentation overload

Nurses and care staff spend a large share of every shift on MDS assessments, care-plan notes, and incident reports rather than on residents. The documentation is mandatory and audit-critical, but it is also the single biggest driver of burnout and turnover in the sector — and the easiest to compress with AI applied to structured capture and summarisation.

02

Chronic staffing shortages and turnover

Long-term care has the highest turnover of any care setting, forcing expensive agency cover and constant onboarding. Demand-aware scheduling, faster credential-checked onboarding, and self-serve leave and roster management measurably reduce agency spend and the administrative load on already-stretched managers.

03

Billing, claims and revenue-cycle leakage

Medicaid, Medicare, NHS and private-pay billing each carry their own coding rules, prior-authorisation steps, and denial patterns. Manual revenue-cycle work leaks margin a facility can't afford; AI applied to coding, claims routing and denials returns it without adding back-office headcount.

04

Resident safety and early deterioration

Falls, pressure injuries, infections and unplanned hospital transfers drive both human harm and regulatory penalties. Remote monitoring with adaptive alerting surfaces deterioration earlier — but only when it integrates with the EHR and the care-team workflow rather than adding another dashboard nobody watches.

05

Privacy, consent and audit obligations

Resident records are special-category data under every major framework. Operators cannot send PHI to a cloud LLM and hope the BAA covers it. Sovereign, on-prem deployment with field-level access control and an immutable audit trail is the only model that survives an inspection.

AI Accelerator Library

Proven accelerators for Long-Term Care

Hm
Health Monitor Agent
Remote patient monitoring with adaptive alerting.
Ps
Patient Scheduler
Demand-aware scheduling that minimises no-shows.
Mp
Medical Records Parser
Extracts structured clinical data from PDFs, faxes and scans.
Cr
Claims Router
Routes claims by payer, plan and likelihood-to-pay.
Pr
Prior Auth Accelerator
Submits, tracks and appeals payer prior authorisations.
Rc
Revenue Cycle Optimizer
Denials, AR days and write-off reduction across revenue cycle.
Ws
Workforce Scheduler
Shift scheduling for retail, BPO and field workforce.
Py
Payroll Processor
Multi-country payroll with statutory-compliance agent.
Dm
DocuMage
Flagship IDP — OCR + ICR + LLM for any document type, replaces legacy OCR.
Re
Redacto
AI-powered redaction of sensitive data across formats.
View full library of 117 accelerators →
Case Studies

Results we've delivered

40% documentation time saved

US senior-living group: MDS and care-note automation

Medical Records Parser and a summarisation layer turned dictated and free-text notes into structured MDS-ready records across forty facilities. Care staff returned roughly forty percent of documentation time to residents; assessment accuracy improved against audit benchmarks.

$4.1M annual recovery

Post-acute network: revenue-cycle and denials recovery

Revenue Cycle Optimizer and Claims Router cut denial rates and AR days across a multi-state post-acute network, recovering several million dollars annually in previously written-off claims with full coding-audit evidence.

26% fewer hospital transfers

Home-health provider: remote resident monitoring

Health Monitor Agent integrated vitals and visit data with adaptive alerting into the care-team workflow. Early-deterioration flags cut unplanned hospital transfers by a quarter over two quarters.

30% less agency spend

Care-home operator: workforce scheduling and onboarding

Workforce Scheduler and OnboardX automated credential-checked onboarding and demand-aware rostering across a regional operator, cutting agency-staffing hours thirty percent and shortening time-to-first-shift for new hires.

Our Services

How we deliver for Long-Term Care

OCR / IDPRPA & AutomationAnalytics & BIGenerative AI

AI for Long-Term Care — let's talk

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