AI operations for healthcare

We translate how your team actually works into AI that actually works.

Start with the work draining your team. Aukera Health helps home care and community-based services organizations clear chart-review backlogs and return nurses to complex cases, coaching, and care.

Proven in a multi-state home-care deploymentWorks with existing electronic medical records · multiple service lines
70%lower cost to serve
99%+target accuracy
4states configured
If this is happening inside your operation

The backlog is not just an operational problem. It is a margin, reimbursement, and clinical-capacity problem.

01

Billable charts are waiting

Review queues slow the documentation-to-reimbursement cycle.

02

Nurses are doing routine approvals

Clinical capacity is consumed by repetitive checks instead of exceptions and quality.

03

Review quality varies

Correction messages depend on who is working, creating rework and weak training signals.

04

Growth means more reviewers

Chart volume and staffing cost rise together, limiting operating leverage.

Implications for leadership
CEO / COOGrow without matching growth in administrative headcount.
CFOTurn delayed billing and clinical labor into operating leverage.
Clinical leadershipKeep judgment with clinicians and standardize routine review.
ITAdd automation without replacing existing clinical systems.
The proof: chart review in production

From growing backlog to continuous, controlled review.

Aukera deployed configurable AI adjudication for a regional medical staffing organization, working with its existing electronic medical record system across multiple service lines.

01 · The challenge

Routine work was crowding the queue.

Rising chart volume created backlogs, inconsistent correction messages, and pressure on clinical reviewer capacity.

02 · The change

AI handled repeatable checks.

Configured rules reviewed routine charts, prepared contextual corrections, and surfaced exceptions for human review.

03 · The result

Nurses focused where they matter.

Reviewers spent more time on edge cases, coaching opportunities, and escalations instead of routine approvals.

Up to 70%lower cost to serveReported in the chart-review case study
“Our team now focuses where it matters most—edge cases, training opportunities, and escalations—rather than routine approvals.”
Operations leadership · medical staffing client

Performance commitment: 99%+ target accuracy, validated monthly · state-specific rules with human review where required.

Read the full case study →
How the team's workload changes

Automate the routine. Support the review. Keep clinical judgment human.

The goal is not to remove your team from chart review. It is to stop asking them to perform every step of every review.

Chart-review task
Today
With Aukera
Owner
Queue intake & prioritizationCollect, sort, and identify aging work.
Manual queue work
Continuous intake
AI
Routine documentation checksApply state, service-line, and required-field rules.
Nurse reads every chart
Reviewed against configured rules
AI
Correction messagingExplain what is missing and what must be corrected.
Written from scratch
Contextual message prepared
AI + nurse
Ambiguous or high-risk chartsResolve clinical nuance and exceptions.
Mixed into the full queue
Surfaced for focused review
Nurse
Coaching, escalation & qualityTurn recurring gaps into better staff performance.
Limited time remains
Time returned to higher-value work
Nurse
Audit trail & SLA trackingRecord decisions, actions, timestamps, and turnaround.
Separate follow-up
Built into the workflow
AI

Oversight is configurable. Routine charts can move automatically where policy permits; human review remains where institutional or state rules require it.

One horizontal capability. Multiple healthcare applications.

Our Healthcare Document Intelligence Platform

From chart intake to the next right action, Aukera reads clinical and operational documents, applies your rules, and works within the systems your teams already use.

STEP 1Ingest Source Data

Read charts, notes, forms, and other data from EHRs and operational systems.

STEP 2Reason & Decide

Apply clinical and operational rules, interpret the data, and determine next steps.

STEP 3Act in Workflow

Post outcomes, prepare corrections, and route alerts or actions in the system of record.

STEP 4Learn & Improve

Capture exceptions, audit trails, and quality signals to refine the operation over time.

Where the platform applies
Prototype / use case

Falls workflows

Check incident details, route follow-up, and escalate clinical or compliance exceptions.

Prototype / use case

Pharmacy script routing

Classify requests, assemble context, route to the right queue, and surface exceptions.

Only chart review is presented as a documented production result. Other areas are vertical or prototype directions.

The team

Healthcare operators building for healthcare operators.

A focused team with the clinical and operational context to turn real work into controlled automation.

Manesh Samtani

Manesh Samtani

Chief Executive Officer & Co-founder

Rodney M. Hamilton, M.D.

Rodney M. Hamilton, M.D.

Chief Strategy Officer & Co-founder

The fastest way to know if this fits

Show us the queue that is consuming your team.

Bring us the workflow, the exceptions, and a sample of the work. We will show you what can be automated, what should stay human, and what the operating case looks like.

Start with your chart-review workflow →