Imagine AI doing the work, and you just approving it.
Chronexa is an AI-native IT services firm. We engineer AI agents, automation and software into how your company runs, so your business grows faster than your headcount.
Anthropic partner. We orchestrate the right model for each job.
01Who we are
Chronexa is an AI-native IT services firm. We design, build and run the AI systems, automations and software that growing companies run on. We have built software for more than ten years. Today we build it alongside AI agents, so we ship in days what used to take months. We don’t sell hype or slide decks. Every engagement has a number attached: hours returned, cost per output cut, revenue unlocked.
02What we do
Choose the work you need done. One team that owns the result.
Strategy, engineering and the people to run it. Pick a practice, or let the free audit tell you where to start.
Most of our work runs under NDA, so clients stay unnamed. What we built and what it changed are below. Outcomes are from delivered work or typical for systems like these.
report-engine · building report
Site photos48 analysed✓
Inspector notes12 pages✓
Component data126 items✓
Financial modelBalanced✓
Component analysis Section 4 of 9
Component
Condition
Remaining
Roof membrane
Fair
6 yrs
Pool resurfacing
Good
9 yrs
Asphalt paving
Poor
2 yrs
Elevator controls
Fair
5 yrs
Draft ready for analyst review · 4 min 12 s
01Report automation · Property engineering
The reports a whole firm is built on, drafted in minutes.
An engineering firm wrote long technical reports by hand from site photos, inspector notes and financial models. We built the engine that reads the photos, extracts every component, runs the numbers, writes the narrative and assembles the finished report. Analysts now review instead of write.
Days → minutes
per report draft
85%
less analyst time
1,200+
reports a year
Computer vision · Claude · n8n · document generation
Invoices, tax forms and data rooms, read the way an expert reads them.
Invoice ingestion with a three-way match for a fintech platform. Tax documents extracted for CPA firms, every field traced to the line it came from. A diligence copilot that reads entire data rooms for a private equity firm. Anything uncertain goes to a person, with the reason.
80%
less manual invoice handling
70%
less data-room review
10–15 min
from intake to engagement letter
Claude vision · citations · OCR · ERP and practice-software integrations
Run 18,204 · success · 3.1 sRun 18,205 · approved by a personRun 18,206 · retried 2× · recovered
03AI orchestration · n8n
35+ production workflows, with recovery designed in.
Our orchestration layer connects models, CRMs, inboxes, calendars, ad platforms and databases. Every workflow ships with retries, a dead-letter queue, monitoring and a human approval step before anything sends, spends or publishes.
Waiting for the editorHow CPA firms survive tax season without hiring
Human approval step
04Marketing engine
A five-agent content team with one human editor.
Search data finds the gap. One agent researches, one writes, one checks every claim, one commissions the artwork, one publishes. The editor approves. The same engine reports on ad spend every morning and flags what changed.
169
articles researched and published
5 → 1
agents to one human editor
9:00 am
daily ad performance brief
Search Console · Exa · Claude · image models · Sanity · Meta Ads API
Saw the Dallas launch. Six recruiter roles open usually means screening is eating the week…
northfield.preview.chronexa.ioBuilt for this prospect
Approved by a person · queued to send
05Sales engine
Every prospect researched, every email personal, a website built for each one.
The engine reads a prospect’s recent news and website, drafts outreach grounded in what it found, and builds a personalised preview website for that prospect. New inbound leads get a reply in seconds. Nothing is sent until a person approves it.
20 min → 40 s
research per prospect
1 site
built per prospect, tracked
Seconds
from form fill to first reply
Apollo · Exa · Claude · Next.js · ManyReach · WhatsApp Cloud API
Every call answered, qualified and booked, at any hour.
Voice agents that sound human, check the live calendar before they offer a slot, book it, and write the call back to your CRM. Built for clinics, home services and any business that loses revenue to missed calls.
Platforms for regulated industries, built to be checked.
A regulatory index for a top-tier law firm that proves it holds every document the regulator has published, and classifies new ones within 30 minutes. A machine-learning trading-signal platform and mobile app for a SEBI-regulated advisor. Court-grade legal translation with human review.
LUMIQOur own skincare brand: strategy, store, photography and film
08Brands & commerce
Brands designed and built end to end, films included.
Brand strategy, store design and build, photography, campaign films and the automation behind the store, from one team using a ten-role AI studio with a senior designer signing off each step. LUMIQ, our own skincare brand, is the reference build.
3
brands live
10
specialist AI roles per build
Weeks
from concept to live store
Shopify · Liquid · Claude · image and video models
LUMIQOur own skincare brand: strategy, store, photography and film
01 / 08
04Why Chronexa
Anyone can prompt AI. Few can make it run a business.
The cost of output has collapsed, yet most companies aren’t growing any faster. With hundreds of people, dozens of tools and years of data, the prompt is the easy part. Everything around it is the work.
01
Someone has to judge the output.
AI answers confidently whether it is right or wrong. We define what “correct” means for your work, test against it, and route anything uncertain to a person.
02
The model is an engineering decision.
Opus, Sonnet, GPT, Gemini, open-weight models: the wrong choice costs ten times more or fails quietly. We pick per task, on accuracy and cost per output.
03
Not everything should be automated.
Some processes aren’t ready and some tools can’t be connected. We start where automation pays back first and tell you what to leave alone.
04
Your data has rules.
Client PII, financial records and privileged documents can’t go into just any model. Residency, redaction, access and audit are designed in from the first day.
05
AI needs context to be useful.
Data schemas, clean pipelines and orchestration across every tool your people use. Without them, chat windows and connectors are a clever intern with no memory.
Five ways to get AI work done.
Every option can produce something. Only one is built to produce outcomes you can measure.
Criterion
In-house team
Independent specialist
Delivery agency
Build with AI tools
Chronexa
Best fit
Long-term core capability
A well-defined specialist task
A scoped delivery programme
Experiments your team can own
Connected AI systems and ongoing engineering
Your responsibility
Hiring and engineering management
Scope and integration ownership
Vendor selection and governance
Architecture, testing and operations
Process expertise and business approvals
Cost to plan for
Compensation, tools and recruiting
Project fee and ongoing maintenance
Build scope and support agreement
Subscriptions and internal engineering time
Agreed build scope, usage and support
Quality to verify
Test coverage and operational readiness
Handover, tests and support
Acceptance criteria and delivery evidence
Evals, security and recovery
Evals, review gates and agreed acceptance tests
After launch
Your team operates it
Agree support separately
Defined by the contract
Your team operates it
Ownership handover; support scoped with you
05What it’s worth
Put a number on it before you spend a dollar.
The same arithmetic we use in the audit. Move the sliders to your company.
Across 46 working weeks. The free audit replaces every assumption here with your real numbers.
6,900hours returned to your team each year
$380kof capacity a year, at today’s cost
3.8full-time people’s worth of work, without hiring
We already use ChatGPT, Claude and Cursor. Why do we need you?
Those tools make one person faster. They don’t make a company run on AI. That takes choosing the right model for each task, connecting AI to your systems and data, building the checks that catch wrong output, and designing for compliance. That engineering is what we do, so your people can run the business instead of the plumbing.
What does an AI-native IT services firm do differently?
We build with AI agents ourselves every day, so we ship in days what traditional firms quote in months. And we measure work by business outcome, the hours, cost per output and revenue it moves, not by hours billed.
What is included in the free first workflow?
We agree one bounded workflow, its connected tools, test data and acceptance criteria during the free audit. You approve that written scope before work starts. Any provider usage, additional integrations and ongoing support are identified separately; further work requires a separate quote.
How do you price?
There are no packages. The audit is free. After it, every build is quoted against the time and revenue it unlocks, and you approve the scope and price before we start.
Can you work with regulated data?
Yes. We have built for legal, tax, financial-services and regulated-advisory teams. We choose models and hosting by where your data is allowed to go, redact what must not leave, keep access scoped, and keep a person approving anything that sends, pays or publishes.
Why don’t you name your clients?
Most of our work runs under NDA. We describe each system by sector, what we built and the outcome, and we are happy to walk you through the engineering on a call.
Who owns what you build?
You do: the code, the workflows, the data and the accounts they run in.
Let AI do the work. We’ll make sure it’s right.
30 minutes with a senior engineer. You’ll leave knowing where AI pays back first in your business, whether or not you hire us.
