AI that gives clinicians their time back — and keeps the care.
We build clinical and life-sciences AI agents that learn from your physicians and researchers — automating scheduling, prior auths, follow-ups, and evidence synthesis, with consent, minimization, and HIPAA-grade access controls built in.
From ambient documentation and prior authorization to clinical guideline surfacing and drug-discovery copilots — grounded on your data, deployed in your environment, and designed so the standard of care rises instead of drifts.
Trusted by teams at
The mandate
Turn patient and research data into action — without adding clinician burden.
Healthcare AI fails when it adds clicks. We design agents around the clinician's and researcher's actual workflow: ambient capture, guideline-grounded suggestions, structured drafts, and one-tap review — with every data flow gated by consent, role, and minimization.
What you get
- Ambient scribe + structured note agents aligned to your specialty and EHR.
- Prior authorization, referral, and follow-up automation with human sign-off.
- Clinical guideline surfacing with citations and patient-specific reasoning.
- Life-sciences research copilots: literature, trials, regulatory, and lab data.
- Private deployments inside HIPAA / GxP / HITRUST-grade environments.
Why it works
Why this approach wins.
01 · Principle
Clinician-first, not clinician-tolerated
Agents listen, draft, and suggest — clinicians approve. Every draft carries sources and rationale. No extra clicks just to get AI's opinion.
02 · Principle
Consent and minimization by construction
Role-based access, de-identification, and consent scopes are wired into the architecture, not bolted on. Audit-ready from day one.
03 · Principle
Research velocity, not research noise
In life sciences, we ground agents on literature, trial data, and regulatory context — with traceable evidence and reproducible outputs scientists can defend.
Outcomes
The outcomes we commit to.
−70%
documentation time
−50%
prior-auth TAT
3×
evidence review speed
100%
auditable access
Awards
Proud moments.
Top 1% on Clutch Global
Top AI Strategy Company 2025
Clutch Fall Champion 2024
Inc. 5000 Fastest Growing
Breakthrough of the Year 2019
Member of Forbes Tech Council
Voice & Speech Recognition 2024
Top Blockchain Company 2024
Innovators of the Year 2019
GoodFirms Top Company
Pain points
Do you recognize your team?
What's happening
- Clinician burnout and attrition are now board-level metrics.
- Prior auth and referrals are bleeding patient experience and revenue.
- Researchers are swamped by literature and trial data updates.
- Your compliance team needs AI governance that actually holds up.
- Competitors are shipping ambient and clinical AI while you're still in pilots.
How it feels
- Protective of patient safety and standard of care.
- Exhausted — clinicians are doing second-shift documentation.
- Cautious about AI hallucinations in clinical context.
- Frustrated that EHR modules "do AI" in name only.
- Hopeful that real relief is finally possible.
Where it hurts
- After-hours charting and documentation debt.
- Prior-auth and referral cycles measured in days.
- Disconnected systems: EHR, PACS, LIS, billing, CRM.
- Siloed research data across labs, studies, and vendors.
- Consent, minimization, and audit duties no one wants to own.
What we ship
Workstreams, real artifacts, measurable outcomes.
Every engagement decomposes into clear workstreams you can ship and measure. Here's the playbook for this segment.
01
Ambient scribe + notes
- Ambient capture
- Specialty templates
- EHR write-back
- Review UX
02
Prior auth & referrals
- Payer playbooks
- Grounded drafts
- Submission + tracking
- Exception workflow
03
Guideline surfacing
- Guideline RAG
- Patient context hooks
- Citations
- Clinician review UX
04
Follow-ups & scheduling
- Outreach agent
- Scheduling hooks
- Consent + opt-out
- Ops dashboard
05
Research & evidence copilot
- Evidence RAG
- Trial + lit connectors
- Reproducibility pack
- Role-based access
As seen in
After-state
What changes on the other side.
Clinicians leave on time with notes signed. Prior auths clear in hours, not days. Researchers navigate literature and trial data with traceable evidence. Every AI interaction is logged, minimized, and consent-scoped — your compliance team sleeps.
How it feels
What becomes possible
- 01Give clinicians back an hour a day without compromising the standard of care.
- 02Turn revenue-cycle bottlenecks like prior auth into a solved workflow.
- 03Compress research and regulatory cycles with grounded, reproducible evidence.
Concerns, answered
The usual concerns — handled.
Concern 01
“We can't send PHI or patient data to public LLMs.”
You don't have to. We deploy inside your HIPAA-grade environment (AWS/Azure/GCP private tenants or on-prem), with de-identification and access scopes enforced at the architecture level.
Concern 02
“AI hallucinations are unacceptable in a clinical setting.”
That's exactly why we ship grounded agents with citations, confidence, and a clinician-in-the-loop UX. No suggestion reaches the chart without review and source.
Concern 03
“Our EHR vendor says they're doing all this already.”
Some of it. We layer on top of Epic / Cerner / Meditech where they stop — custom workflows, specialty-specific drafts, and cross-system agents the vendor won't build.
Concern 04
“GxP / FDA scrutiny will slow any AI down in life sciences.”
We design for GxP, 21 CFR Part 11, and reproducibility from day one — data lineage, versioning, audit, and validation packs are part of the build, not an afterthought.
Alternatives
Why us and not…
EHR-native AI modules
Broad but shallow. We build into the workflow and specialty that the EHR leaves generic.
Ambient-scribe startups
Often a single point product. We extend ambient capture into prior auth, follow-ups, and research.
Big-4 healthcare consulting
Great roadmaps, thin on production AI. We hand you running agents, not PowerPoints.
Case studies
Where ideas become impact.
Behind every system we ship is a team that moved from uncertainty to measurable outcomes. A few recent ones.
Case 01 · Client
Wealth Management Company
Objective
The goal was to integrate AI tools into everyday work across all roles and increase overall productivity.
Results
85%
of employees use AI tools daily in workflows
70%
of routine queries resolved via GPT assistant within the first 2 weeks
5 min
Average response time reduced from 1 hour to 5 minutes
52
ready-to-use prompts created for key scenarios (finance, presale, legal, HR)
12
AI agents deployed for quality, sales, finance, and executive dashboards
100%
prompts reviewed for data security compliance
Stack
ChatGPT Enterprise, n8n, Cursor, RAGDB (vector database), Power BI + Bloomberg GPT, Miro, Whisper / Coqui
Case 02 · Client
E-Commerce Platform
Objective
Automate customer support and optimize product recommendation systems using AI.
Results
60%
reduction in customer support tickets
3x
increase in product recommendation conversion rate
24/7
Automated support coverage with AI chatbot
8
custom AI workflows deployed across departments
40%
faster content generation for marketing campaigns
95%
customer satisfaction score with AI-assisted support
Stack
Anthropic API, LangChain, Pinecone, Next.js, Vercel, PostgreSQL, Redis, NanoClaw
Founder & team
Senior humans,
AI-native craft.
100+
people trained
20+
companies transformed
9.4/10
avg. workshop rating
96%
AI adoption in 7 days
Talk to the founder
Mike Doroshenko
Product strategist and AI consultant with 10+ years of digital product strategy and AI transformation. Author of corporate training programs used by leading companies.
Supported by 30+ experts
from McKinsey, Google, and top tech companies.
Testimonials
Our clients said it best.
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CEO, SECTOR 31 s.r.o.y
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Philipp Lenz
Co-Founder, parloo.de
“There are a lot of companies that offer similar services but we've had an end-to-end good experience with them.”
Patrik Dvořák
CEO, SECTOR 31 s.r.o.y
“Vahue's responsiveness and accuracy were impressive. We highly recommend them”
Jacob Berg
CTO at Social Curator
“I appreciated the level of comfort Vahue made us feel. It was like being a part of a family.”
Georg Winkler
CEO, Xpertify
“The different and very profound skillset of the Vahue team was very impressive.”
Prasanna Elvis Eswara
Principal Consultant, Roost Digital
“They were proactive and seemed eager to build a relationship.”
Jacob Berg
CTO at Social Curator
“I appreciated the level of comfort Vahue made us feel. It was like being a part of a family.”
Georg Winkler
CEO, Xpertify
“The different and very profound skillset of the Vahue team was very impressive.”
Prasanna Elvis Eswara
Principal Consultant, Roost Digital
“They were proactive and seemed eager to build a relationship.”
Bartek Czerwinski
CTO, Quik
“Vahue has the ability to dive in and get the work done creatively with a lot of personal input.”
Steinar Aas
CEO & Co-Founder at Asio AS
“Their flexibility and genuine interest in finding the best solution for the product was impressive.”
Georg Winkler
CEO, Xpertify
“The different and very profound skillset of the team was very impressive.”
Bartek Czerwinski
CTO, Quik
“Vahue has the ability to dive in and get the work done creatively with a lot of personal input.”
Steinar Aas
CEO & Co-Founder at Asio AS
“Their flexibility and genuine interest in finding the best solution for the product was impressive.”
Blog
Perspectives that matter.
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A practical guide to integrating large language models with sensitive business data while staying compliant and secure.
Evaluating Code Data Sources for Training Large Language Models
A practical comparison of the major code dataset sources — from open-source repos to dedicated coding teams — and how to choose the right one.
The Case for Human-Written Code in LLM Training
Why human-authored code remains essential for building reliable coding assistants — and where synthetic data falls short.
Contact
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