AI automation · Amsterdam → worldwide
Your team has better things to do than copy-paste.
X-GenAI builds custom AI agents and workflow automation, the kind that keeps working after the demo ends.
15 minutes, no pitch deck. Just bring your most annoying workflow.
AGENT ORCHESTRATOR · SUPPORT_TRIAGE_V1
RUNNINGTRIGGER
ticket.created
AI AGENT
classify · route
AUTO-REPLY
docs match
ESCALATE
human review
CRM SYNC
write-back
TICKETS TODAY
1,042
AVG RESPONSE
412ms
ESCALATION RATE
0.18%
▸ ticket #1042 received · classifying intent
✓ matched to docs · replied in 4s
▸ ticket #1043 flagged · refund, needs sign-off
Illustrative run: shows how X-GenAI structures an agent pipeline, not a specific client's live data.
One agent · one Tuesday morning
While your team grabbed coffee before standup
- 8:4114 support tickets came in overnight
sorted and prioritized before anyone logged in
- 8:4711 routine ones answered
straight from your docs, in your tone of voice
- 8:52One refund case set aside
policy says a human decides, so a human will
- 8:58Summary posted to #support
one tidy message instead of forty pings
By the time the coffee kicked in, the queue was already empty. Nobody noticed. That's the point.
Model-agnostic by design. Built with:
What would your week look like if the boring parts ran themselves?
What the research says
The shift to AI automation, in numbers.
What research firms and the companies building this technology are finding, on where AI automation is already paying off.
“92% of companies plan to increase AI investment over the next three years, but only 1% call their deployment mature.”
· McKinsey, Superagency in the Workplace, Jan 2025
“Companies that align AI, platform, and business strategy see 2.2x the revenue growth of their peers.”
· Accenture, Platform Strategy in the Age of Agentic AI, Dec 2025
“82% of CEOs are now more optimistic about AI's ROI than they were a year ago.”
· BCG, AI Radar 2026
“Median time-to-value on agent deployments is about 5.1 months.”
· BCG · Forrester, 2026
“Only 25% of AI initiatives deliver their expected ROI, and just 16% have scaled enterprise-wide.”
· IBM Institute for Business Value
“88% of enterprises say AI has already increased annual revenue in some or all parts of the business.”
· NVIDIA, State of AI 2026
“NVIDIA agreed to acquire Hugging Face (18M+ developers, 3M+ models, 200K+ enterprise customers) for about $13 billion.”
· NVIDIA / Bloomberg, Sept 2026
“Anthropic's annualized revenue run rate hit $65 billion in July 2026, up from $30 billion just three months earlier.”
· Anthropic, via CNBC, Aug 2026
“52% of executives say their organization has already deployed AI agents in production.”
· Google Cloud, ROI of AI Study 2025
“Google shipped Gemini 3.8 Flash, its third Flash model in six weeks, built for coding and agentic tasks.”
· Google DeepMind, Sept 2026
“Meta's business AI tools went from 1 million to 10 million weekly conversations in a single quarter.”
· Meta, 2026
“Meta launched Muse, its first personal AI agent, across web, iOS, Android, and WhatsApp.”
· Meta, Sept 2026
“OpenAI released GPT-6 Astra, built for computer use, browsing, and software engineering, rolling out across ChatGPT, the API, Azure, and Bedrock.”
· OpenAI, Sept 2026
“By 2026, 40% of enterprise apps will ship with task-specific AI agents, up from less than 5% in 2025.”
· Gartner, Aug 2025
“$234 billion in enterprise application software spend is now at risk from agentic AI.”
· Gartner, July 2026
“Workforce access to AI grew from under 40% to around 60% of workers in a single year.”
· Deloitte, State of AI in the Enterprise 2026
“Uber burned through its entire 2026 AI budget in just four months, as Claude Code adoption spread across engineering faster than finance had modeled.”
· Uber, via Fortune, May 2026
“Early results from Booking.com's new agentic messaging tools showed a 73% increase in partner satisfaction over previous tooling.”
· Booking.com Newsroom, 2026
“ServiceNow customers running agentic AI in production grew 9x in a single quarter compared with nine months earlier.”
· ServiceNow, Q2 2026 earnings
“Salesforce's Agentforce reached about $800 million in annual recurring revenue by the end of FY26, up 169% year over year.”
· Salesforce, Q4 FY26 earnings
“JPMorgan Chase's AI initiatives are already delivering about $2 billion a year in cost savings.”
· JPMorgan Chase, Jamie Dimon, 2026 shareholder letter
“Amazon now runs more than one million robots across its warehouses, nearly one for every 1.5 human workers.”
· Amazon, Andy Jassy, Q1 2026 earnings call
“Microsoft 365 Copilot passed 30 million paid seats, with net seat additions more than doubling quarter over quarter.”
· Microsoft, Satya Nadella, FY26 Q4 earnings call, July 2026
“Mastercard launched Agent Pay for Machines, a network for AI agents to make high-frequency, low-value payments to each other, backed by more than 30 partners including Stripe, Coinbase, and Adyen.”
· Mastercard Newsroom, June 2026
“Customers who use Walmart's Sparky AI shopping agent have an average order value about 35% higher than customers who don't.”
· Walmart, John Furner, Q4 FY26 earnings call, Feb 2026
“OpenAI's enterprise revenue overtook its consumer revenue for the first time, after starting 2026 in a 60-40 split favoring consumer.”
· OpenAI, Sarah Friar, via CNBC, Aug 2026
“Anthropic's annualized revenue run rate is pacing to top $100 billion in 2026, up from $65 billion just two months earlier and more than 10x where it stood at the end of 2025.”
· Anthropic, via The New York Times, Sept 2026
“Nearly three-quarters of Google Cloud customers are already using its AI products, and those customers are spending about 50% more than their original commitments.”
· Google Cloud CEO Thomas Kurian, via CNBC, Sept 2026
“NVIDIA launched an open-source Agent Toolkit for autonomous, self-evolving enterprise AI agents, with Adobe, Cisco, SAP, Salesforce, ServiceNow, and Siemens among the partners already building on it.”
· NVIDIA Newsroom, Mar 2026
“Two-thirds of CIOs and CTOs say they're held accountable for AI systems they don't fully control, and 70% say business teams are deploying AI faster than IT can track.”
· IBM Institute for Business Value, via IBM Newsroom, June 2026
“92% of companies plan to increase AI investment over the next three years, but only 1% call their deployment mature.”
· McKinsey, Superagency in the Workplace, Jan 2025
“Companies that align AI, platform, and business strategy see 2.2x the revenue growth of their peers.”
· Accenture, Platform Strategy in the Age of Agentic AI, Dec 2025
“82% of CEOs are now more optimistic about AI's ROI than they were a year ago.”
· BCG, AI Radar 2026
“Median time-to-value on agent deployments is about 5.1 months.”
· BCG · Forrester, 2026
“Only 25% of AI initiatives deliver their expected ROI, and just 16% have scaled enterprise-wide.”
· IBM Institute for Business Value
“88% of enterprises say AI has already increased annual revenue in some or all parts of the business.”
· NVIDIA, State of AI 2026
“NVIDIA agreed to acquire Hugging Face (18M+ developers, 3M+ models, 200K+ enterprise customers) for about $13 billion.”
· NVIDIA / Bloomberg, Sept 2026
“Anthropic's annualized revenue run rate hit $65 billion in July 2026, up from $30 billion just three months earlier.”
· Anthropic, via CNBC, Aug 2026
“52% of executives say their organization has already deployed AI agents in production.”
· Google Cloud, ROI of AI Study 2025
“Google shipped Gemini 3.8 Flash, its third Flash model in six weeks, built for coding and agentic tasks.”
· Google DeepMind, Sept 2026
“Meta's business AI tools went from 1 million to 10 million weekly conversations in a single quarter.”
· Meta, 2026
“Meta launched Muse, its first personal AI agent, across web, iOS, Android, and WhatsApp.”
· Meta, Sept 2026
“OpenAI released GPT-6 Astra, built for computer use, browsing, and software engineering, rolling out across ChatGPT, the API, Azure, and Bedrock.”
· OpenAI, Sept 2026
“By 2026, 40% of enterprise apps will ship with task-specific AI agents, up from less than 5% in 2025.”
· Gartner, Aug 2025
“$234 billion in enterprise application software spend is now at risk from agentic AI.”
· Gartner, July 2026
“Workforce access to AI grew from under 40% to around 60% of workers in a single year.”
· Deloitte, State of AI in the Enterprise 2026
“Uber burned through its entire 2026 AI budget in just four months, as Claude Code adoption spread across engineering faster than finance had modeled.”
· Uber, via Fortune, May 2026
“Early results from Booking.com's new agentic messaging tools showed a 73% increase in partner satisfaction over previous tooling.”
· Booking.com Newsroom, 2026
“ServiceNow customers running agentic AI in production grew 9x in a single quarter compared with nine months earlier.”
· ServiceNow, Q2 2026 earnings
“Salesforce's Agentforce reached about $800 million in annual recurring revenue by the end of FY26, up 169% year over year.”
· Salesforce, Q4 FY26 earnings
“JPMorgan Chase's AI initiatives are already delivering about $2 billion a year in cost savings.”
· JPMorgan Chase, Jamie Dimon, 2026 shareholder letter
“Amazon now runs more than one million robots across its warehouses, nearly one for every 1.5 human workers.”
· Amazon, Andy Jassy, Q1 2026 earnings call
“Microsoft 365 Copilot passed 30 million paid seats, with net seat additions more than doubling quarter over quarter.”
· Microsoft, Satya Nadella, FY26 Q4 earnings call, July 2026
“Mastercard launched Agent Pay for Machines, a network for AI agents to make high-frequency, low-value payments to each other, backed by more than 30 partners including Stripe, Coinbase, and Adyen.”
· Mastercard Newsroom, June 2026
“Customers who use Walmart's Sparky AI shopping agent have an average order value about 35% higher than customers who don't.”
· Walmart, John Furner, Q4 FY26 earnings call, Feb 2026
“OpenAI's enterprise revenue overtook its consumer revenue for the first time, after starting 2026 in a 60-40 split favoring consumer.”
· OpenAI, Sarah Friar, via CNBC, Aug 2026
“Anthropic's annualized revenue run rate is pacing to top $100 billion in 2026, up from $65 billion just two months earlier and more than 10x where it stood at the end of 2025.”
· Anthropic, via The New York Times, Sept 2026
“Nearly three-quarters of Google Cloud customers are already using its AI products, and those customers are spending about 50% more than their original commitments.”
· Google Cloud CEO Thomas Kurian, via CNBC, Sept 2026
“NVIDIA launched an open-source Agent Toolkit for autonomous, self-evolving enterprise AI agents, with Adobe, Cisco, SAP, Salesforce, ServiceNow, and Siemens among the partners already building on it.”
· NVIDIA Newsroom, Mar 2026
“Two-thirds of CIOs and CTOs say they're held accountable for AI systems they don't fully control, and 70% say business teams are deploying AI faster than IT can track.”
· IBM Institute for Business Value, via IBM Newsroom, June 2026
How one real workflow actually runs
Input → workflow → review → result
Not illustrative, this is the enquiry-to-CRM automation built and tested for real, synthetic-data proof. See the full run →
An enquiry comes in
A contact-form submission or lead-gen webhook: messy, sometimes incomplete, sometimes a duplicate delivery.
Validated, deduped, classified
Schema-checked before anything else happens. Already-seen enquiries are skipped, not re-processed. The rest gets classified, with the enquiry text always treated as data, never as instructions.
Anything uncertain goes to a human
Missing fields, ambiguous intent, or a message that tried to manipulate the pipeline: all routed to a review queue instead of guessed into a record.
A clean record, or a logged reason why not
Everything else becomes a CRM record with a drafted (never auto-sent) acknowledgement. A provider failure is visible and logged, not silent.
What X-GenAI does
Services
Seven ways X-GenAI helps, matched to what your team needs, not a fixed package.
001 / 007
AI Agents & Automation
Custom agents and workflow automation that take real work off your team: scoped, built, and shipped to production. You own the result.
$ scope workflow --client onboarding
> 3 automatable steps found · 2 review gates
$ deploy --env production
> shipped · logging on · eval set attached
$ ▋
002 / 007
AI Consulting
Before anything gets built, what's worth automating in your workflows gets mapped, along with what each piece would cost, so budget goes where it pays off.
Opportunity map · draft
Ticket triage
20–40 hrs to build
Onboarding emails
15–25 hrs to build
Contract review
N/A
003 / 007
AI Education & Content
The blog and newsletter track what's changing in AI: real advancements, not hype, so you can tell the difference before you spend on it.
This week's issue
TypeSafe's Jev is a model that doesn't write. Here's why that matters.
Is this task worth automating? What the field studies say
Should you get better at prompting, or better at judging the output?
004 / 007
Responsible & Climate-Conscious AI
The smallest model that reliably does the job, not the biggest one that impresses in a demo. Inference tuned to match: caching, batching and routing each request to the cheapest model that passes. Steps that only need a decision go to a decision model like Jev, which answers without generating any text. Lower bills and a smaller footprint, by default.
Model choice · default
005 / 007
AI Analytics & Evaluation
See what your AI is doing and what it costs. Token analytics down to each feature and customer, AI analytics on quality, latency and usage, and independent evals for systems in production or still a prototype, yours or ours. Drift alerts catch a regression before your users do.
Analytics + eval run · nightly
Illustrative run: shows the kind of analytics and eval harness X-GenAI builds, not a measured result from a specific client system.
006 / 007
Custom AI Products
GenAI and agentic apps, built from your idea: assistants, copilots, document tools and apps where agents do the work. We take it from first sketch to something people can sign up for and pay for, with the design, the AI inside it, payments and hosting. You own the code and the product.
Product build · plan
Prototype
clickable, in front of real users
AI features
the part that makes it worth paying for
Accounts & payments
sign up, subscribe, invoice
Launch
hosting, monitoring, first customers
007 / 007
Agent Engineering
The setup that makes AI agents useful inside your business: custom MCP servers that connect them to your tools, skill files that teach them your processes, clear specs for what each agent does, and the harness around them with permissions, hooks and logging. Then an agent manager to run them: which agents are live, what each one may touch, what they cost, and how a team of agents hands work to each other.
Proof, not a pitch
Two demos, actually running
Self-built, not a case study, X-GenAI has no clients yet to claim results from. Both outputs below are copied verbatim from an actual run, not written by hand.
01 / Working demo
Onboarding Agent
Every new signup gets triaged the moment it happens: persona classified and activation risk scored by plain, readable rules, then a personalized welcome email drafted by Claude. If an account goes quiet, the agent drafts a Slack alert for CS, it never contacts an at-risk customer itself. A human always makes the save call.
cs-activation-alerts
🔴 Nordfleet Logistics (Scale) has gone 91h with zero activation, flagging before this reads as churn. Suggest a personal outreach call re: “enterprise rollout / SSO,” not another automated email.
02 / Working demo
Client-Reporting Automation
Every metric (CTR, cost per conversion, week-over-week deltas) is computed deterministically from raw campaign data, never touched by the model. Claude only narrates the facts that computation already flagged, so the summary can't invent a number that just sounds plausible.
Marlowe & Finch Law
🔴 At risk“This week's clear win: average tracked keyword rank improved from 9.6 to 8.2. The thing worth your attention: conversions dropped -35.3% week-over-week (34 → 22).”
“Northstar Analytics” and “Marlowe & Finch Law” are fictional, invented for these demos, same disclosure the rest of this site uses for illustrative work. Every number above is computed for real from sample data; only the surrounding prose runs from a template without a live Claude API key. The source lives in X-GenAI's working repo, which also holds unreleased pricing and outreach material, so it isn't public, happy to walk through the actual code on a call.
See the most rigorously tested one: hardened against bad input & prompt injection →Why it holds up
Built for what happens after the demo.
Working together
Clear scope at every stage, no lock-in. Five steps, and you can stop after any of them.
Start here
Discovery Audit
X-GenAI maps what's worth automating in your workflows and what each piece would cost.
Stage 1 of 5: Discovery Audit
Most “AI automation” looks great in the demo and falls apart the first week it meets your real data. X-GenAI would rather ship you something boring, the kind where it just… works.