AI agents that read your policies — and ship claims faster.
We build reliable insurance AI agents that learn your underwriting and claims context, accelerate decisions, and keep a human firmly in the loop — with access controls your auditors trust.
From FNOL intake to underwriting, policy servicing, fraud, and subrogation — grounded on your policy docs and playbooks, wired into your core admin system, and measured on loss-adjusted accuracy, not demo wow.
Trusted by teams at
The mandate
Turn unstructured insurance work into fast, explainable, reviewable decisions.
Insurance is drowning in PDFs, emails, ACORDs, medicals, and endorsements. We deploy agents that read, classify, extract, reason over policy and playbook, and draft decisions — then route to humans for sign-off with every source and rationale attached.
What you get
- FNOL + claims intake: multimodal extraction across PDFs, photos, emails, voice.
- Underwriting copilots grounded on your guidelines, appetite, and rating docs.
- Policy-servicing agents for endorsements, certificates, and renewals.
- Fraud / SIU triage with rationale, links, and reviewable evidence.
- Subrogation + recovery agents surfacing leakage and missed opportunities.
Why it works
Why this approach wins.
01 · Principle
Agents that actually read the policy
Not a generic LLM — a grounded agent that cites the clause, the endorsement, the exclusion, and your internal playbook side-by-side.
02 · Principle
Human-in-the-loop is a feature, not a disclaimer
Every decision carries confidence, rationale, sources, and a structured review UX so adjusters and underwriters approve in seconds, not minutes.
03 · Principle
Ships into your core, not around it
We integrate with Guidewire, Duck Creek, Majesco, Sapiens, and homegrown cores — so the agent's output lands in the system your ops already live in.
Outcomes
The outcomes we commit to.
−50%
claims cycle time
+30%
underwriter capacity
3×
FNOL triage speed
100%
cited decisions
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
- Combined ratio is under pressure and ops spend keeps climbing.
- A CAT event exposed how fragile manual intake really is.
- Underwriters are the bottleneck for every growth plan.
- Customers churn because FNOL and servicing feel 20 years old.
- Regulators are asking how your AI decisions get made.
How it feels
- Skeptical — you've seen too many "AI" demos that fail on a real claim.
- Pressured — leadership wants digital transformation without risk.
- Frustrated — talent can't scale with submission volume.
- Protective — one mispaid claim is a headline risk.
- Envious of insurtechs shipping instant quotes and instant claims.
Where it hurts
- ACORDs, PDFs, and emails that slow every workflow.
- Underwriters context-switching across 8+ systems per submission.
- Leakage on subrogation, fraud, and duplicate claims.
- Core systems that resist modern tooling.
- No consistent audit trail for AI-assisted decisions.
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
FNOL & claims intake
- Multimodal extractor
- Core integration
- Confidence + review UX
- Audit log
02
Underwriting copilot
- Grounded RAG
- Rating + rules hooks
- Decision rationale
- Supervisor view
03
Policy servicing agent
- Servicing agent
- Document generation
- Exception workflow
- Customer UX
04
Fraud & SIU triage
- Signal library
- Link analysis
- Case rationale
- Investigator queue
05
Subrogation & recovery
- Recovery detector
- Demand drafts
- Evidence pack
- Review workflow
As seen in
After-state
What changes on the other side.
Claims cycle time cuts in half. Underwriters run 30% more submissions without hiring. Every AI decision lands in Guidewire / Duck Creek / your core with citations and reviewer sign-off. Fraud and subrogation stop leaking quietly.
How it feels
What becomes possible
- 01Modernize claims without replacing your core.
- 02Grow premium without linearly growing underwriting headcount.
- 03Turn loss-adjustment data into a durable competitive advantage.
Concerns, answered
The usual concerns — handled.
Concern 01
“We've been burned by RPA and early AI — don't see what's different.”
We ship grounded, evaluated agents with a human review UX and full citation trails. Not brittle scripts and not black-box LLMs — engineered for the insurance reality.
Concern 02
“Our core (Guidewire / Duck Creek / homegrown) is a fortress.”
We've wired agents into all of them. We integrate via sanctioned APIs, event buses, or controlled workflows — so the agent lives where your ops already live.
Concern 03
“Regulators will kill anything touching underwriting or claims.”
We design for explainability and audit from day one: cited sources, confidence, rationale, and logs. Regulators see evidence, not promises.
Concern 04
“Our data is messy and siloed.”
That's exactly the problem we're good at. Multimodal extraction, data contracts, and lightweight pipelines — we bring clean signal out of the mess.
Alternatives
Why us and not…
Horizontal insurtech platforms
Opinionated products; hard to fit your line of business. We build into your core and your playbook.
Big-4 insurance consulting
Heavy on roadmap, light on running agents. We ship production systems your ops actually use.
Generic RPA / doc AI vendors
Extract fields but don't reason. We add grounded decisioning with citations and review UX.
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.
Patrik Dvořák
CEO, SECTOR 31 s.r.o.y
“Vahue's responsiveness and accuracy were impressive. We highly recommend them”
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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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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