PROOF OF PROGRESS
Proof of progress, at scale.
- 5,000+paid-for leads recovered from leaksFound in client CRMs and put back into the pipeline, with the leak closed for good
- 100,000+CRM records re-attributed and taggedEvery lead traced to the ad and source that produced it, verified before and after
- +40%AI citationssearch visibility and AI citationsA leading business education brand, across Google and YouTube (founder-attested)
- −45%$23.51cost per booked appointment on the best dayAfter full server-side tracking and CRM repair: vs a $42.62 pre-takeover average
- Full CAPIserver-side conversions live for clientsMeta Conversions API and CRM outcomes fed back so the ad algorithms learn from real sales
- Same dayfailures caught by AI growth intelligenceDaily data visualisation and readouts that name what changed and why
Client names stay confidential. Per-client figures link to the study behind them.
HYPER-CONTEXTUAL, NOT GENERIC
Built on four kinds of context only your business has.
A generic assistant answers questions. Contextual AI knows which numbers matter here, who owns them and where the process leaks, so it can prepare the next move instead of another report.
- 01Your data
CRM, ad accounts, analytics, calendars and finance, read through their own APIs, not screenshots.
So the AI works from the numbers you actually run on - 02Your people
Who owns each outcome, who approves, who needs to know, and what each role can see.
So nothing consequential happens without the right person - 03Your process
The real path from first touch to sale and renewal, including the handoffs where value leaks.
So automation lands on the step that limits revenue - 04Your decisions
The few numbers leadership decides on, and the thresholds that should trigger a call.
So reports end in a decision, not a dashboard
FUTURE-PROOF, NO FOMO
Stop worrying about missing the next AI wave.
New models arrive every month. With a model-agnostic implementation, each one is a free upgrade to a system that already knows your business: faster, smarter and cheaper to run, without starting over.
- 01Model-agnostic by design
Your context, rules, approvals and measurements live in your own operating layer, not inside one vendor's model. Any capable model can plug into it.
- 02Every new model is an upgrade
When a faster, smarter or cheaper model ships, we swap it in behind the same gates and readouts. Your system improves; nothing is rebuilt.
- 03Your advantage compounds
The context we capture about your business, what works, what leaks, who decides, keeps growing. Better models only make more of it.
- 04No chasing, no lock-in
You never need to track every launch or bet on a winner. We test what is new against your numbers and adopt it only when it moves them.
SECURITY, BLAST RADIUS AND COMPLIANCE
AI you can trust inside the business.
Growth work touches the systems that hold customers, money and reputation. We contain every AI system by design, and because we work across ad accounts, CRMs, websites and data, we routinely uncover security issues the business did not know it had: exposed keys, over-permissioned accounts, missing backups and consent gaps.
We work closely with security specialists to turn what we find into short, prioritised recommendations a team can actually implement, drawing on IT disaster-recovery planning for foundations, a national automotive brand and other large organisations.
- 01Blast radius mapped first
Before any AI touches a system we map what it could reach, change or leak if it misbehaved, and shrink that radius before anything goes live.
- 02Contained by design
Least-privilege, scoped credentials for every agent; read-only by default; separate environments; audit logs of every action; an off switch that works.
- 03Approval gates on consequence
Anything that spends money, contacts a customer, changes a record or moves data outside the business waits for a named person.
- 04Your data stays yours
Client data is never used to train shared models. Access is logged, time-bound and revocable.
- 05Compliance kept, not assumed
Consent, privacy and retention rules are built into tracking, CRM and AI workflows, so growth work does not create regulatory exposure.
PRINCIPLES FIRST
The principles are fixed. The sequence is not.
Five principles hold on every engagement. What changes is the order of the work: it is modelled from the facts, and re-sequenced every time a readout comes in.
- 01One owner per outcome
Every AI system has a named person accountable for what it does and what it changes.
- 02Evidence before automation
A process is measured and understood before it is automated. Automating a broken step only hides the break.
- 03People approve consequential actions
AI drafts, prepares and monitors; anything that spends money, contacts a customer or changes a record passes an approval gate.
- 04Every step is measured
Each change ships with the number it should move and a readout of what it actually moved.
- 05Context is kept, not rebuilt
Decisions, sources and reasons are recorded, so the next person and the next model start from what is already known.
- 01Model the business→
- 02Rank the constraints→
- 03Ship the smallest change→
- 04Read the result→
- 05Re-sequence
WHAT WE IMPLEMENT
AI where it moves revenue, leads and appointments.
Each system is chosen for the constraint it relieves and tagged with the number it should move. See CHIEF V0.29, our AI operating system
- 01Daily executive intelligence
A morning read of spend, leads, bookings and sales that names what changed and why.
Moves: speed of the next decision - 02AI agents inside approval gates
Lead response, follow-up drafting, research and monitoring, bounded by owner-approved rules.
Moves: speed to lead and booked appointment rate - 03CRM automation and lead routing
Every lead captured, owned and followed up by rule, with duplicate-safe workflows.
Moves: leads that turn into opportunities - 04Measurement the ad platforms learn from
Server-side conversions, full Meta Conversions API and CRM outcomes sent back to the algorithms.
Moves: cost per booked appointment - 05Content and creative with review
Research, drafts and variations produced fast, published only after a person approves.
Moves: cost per lead and search visibility - 06A governed context layer
CHIEF, our operating system that keeps the business's context, evidence and approvals in one place.
Moves: every number above
Questions leaders ask
What is contextual AI implementation?
AI built and configured around one business's own data, people, process and decisions, rather than a generic tool the team has to adapt to. It starts from how the business actually runs and what limits its revenue.
How do you decide what to implement first?
We model the business, rank the constraints by their effect on revenue, and ship the smallest change that moves the top one. The readout decides the next step, so the sequence changes as the facts do.
How do you prove progress?
Every change ships with the number it should move and a measured readout from the source systems, such as the CRM and the ad accounts. If a step does not move its number, we say so and re-sequence.
Will our AI become outdated as new models come out?
No. The implementation is model-agnostic: your data, context, rules and measurements sit in your own operating layer, and models plug into it. When a better model ships, we test it against your numbers and swap it in, so every advance makes your system faster, smarter and cheaper instead of obsolete.
How do you keep AI safe and compliant?
Every AI system is contained by design: its blast radius is mapped before launch, it runs on least-privilege, scoped credentials, read-only by default, with audit logs and approval gates on anything consequential. Client data is never used to train shared models, and consent, privacy and retention rules are built into the workflows.
Does AI act without approval?
No. AI drafts, prepares, monitors and routes; anything that spends money, contacts a customer or changes a record passes an approval gate owned by a named person.