An agentic back-office that runs — with audit.
We replace repetitive ops work — AP/AR, procurement, HR, ticketing — with agents wired into your ERP/ITSM and a full audit trail your finance team will love.
From invoice capture to vendor onboarding to HR ticketing, we build the workflows that fire without a human in the loop, and escalate cleanly when they shouldn't.
Trusted by teams at
The mandate
Move repeatable ops work to agents; keep judgment work with humans.
If a process has a decision tree and a system of record, an agent can run it. We scope micro-jobs (one invoice type, one vendor flow, one HR ticket family), ship them, and compound — with full audit, rollback, and SOD baked in.
What you get
- Agentic workflows over NetSuite/SAP/Oracle/Workday/ServiceNow.
- Document understanding: invoices, POs, contracts, KYC forms.
- Exception handling with human-in-the-loop escalation.
- Audit trail, SOD controls, and reversibility on every action.
- Adoption dashboards: throughput, STP rate, cycle time, error rate.
Why it works
Why this approach wins.
01 · Principle
Every action is auditable
No mystery: each agent decision is logged with inputs, model version, tools called, and who/what approved it. Finance and audit get clean trails, not black boxes.
02 · Principle
Exceptions route to the right human
Agents know when they don't know. Confidence thresholds, SOD rules, and escalation paths mean edge cases land in a queue, not in the void.
03 · Principle
ERP/ITSM stays in charge
We don't rip and replace. Agents read and write via your existing systems; your source of truth doesn't move.
Outcomes
The outcomes we commit to.
70–90%
straight-through rate
−50%
cycle time
<1%
rework rate
100%
auditable
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
- Month-close is bleeding overtime.
- Procurement backlog blocking sales.
- A BPO contract renewal is staring at you.
- HR ticket SLAs slipping after headcount growth.
How it feels
- Exhausted by spreadsheets as glue.
- Anxious about compliance on manual workflows.
- Skeptical of “RPA 2.0” pitches that underdeliver.
- Frustrated that ERP vendors quote 12-month projects.
Where it hurts
- Data trapped in PDFs and email threads.
- Copy-paste between ERP, ITSM, and spreadsheets.
- Manual approvals that no one actually reviews.
- Audit findings from broken controls.
- BPO costs rising faster than volume.
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
AP / AR automation
- Invoice OCR + extraction
- PO match agent
- Posting integration
- Exception queue
02
Procurement flows
- Intake bot
- Vendor KYC
- Policy guardrails
- PO agent
03
HR ops
- HR copilot
- Policy RAG
- Ticket router
- Onboarding agent
04
ERP / ITSM overlay
- Integrations
- Action log
- SOD rules
- Audit export
As seen in
After-state
What changes on the other side.
Month-close happens without firefighting. BPO spend drops. Your ops team runs a queue of exceptions, not a treadmill of data entry. Auditors get a clean export.
How it feels
What becomes possible
- 01Cut BPO spend 30%+ without reducing throughput.
- 02Shrink close from 10 days to 3.
- 03Scale into new regions without linearly adding ops staff.
Concerns, answered
The usual concerns — handled.
Concern 01
“We've been burned by RPA before.”
Agentic workflows fail differently from brittle RPA. We budget for drift, log every action, and version prompts + tools like code.
Concern 02
“Our ERP is SAP — integrations take forever.”
We've shipped against SAP, Oracle, NetSuite, Workday. We use your existing APIs and iPaaS; the agent is the thin layer, not the platform.
Concern 03
“Compliance will block anything touching finance.”
SOD, audit trails, reversibility, and human-in-loop are architectural defaults — we write the controls memo in week one, not week ten.
Concern 04
“Our processes are too non-standard.”
Non-standard is where agents beat RPA. We read your SOPs, emails, and tickets as context — we don't force them into a template.
Alternatives
Why us and not…
UiPath / Automation Anywhere
Brittle rule-based bots. Agents handle the ambiguity RPA can't.
Big-4 BPO
Linear cost, slow iteration. We build the system; you keep the margin.
ERP-native automation
Only covers happy paths. We solve the exception tail.
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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