AI that does a real job in your business.

The problem. Operators raise invoices in Books without linking them to a CRM deal. The bookkeeper can't tell which deals paid. Sales reports lie. Marketing can't see which clients actually produced revenue. Demand Reactivation can't tell who has gone quiet because the data is broken.

What runs. The Daily Sync Agent walks the Zoho Books to Zoho CRM bridge three times a day, matches invoices to deals via the zcrm_account_id bridge (never by name), and pings the team only when something is genuinely ambiguous.

Where the value flows. Invoicing audit-clean. Sales reports finally true. Marketing sees revenue by segment, not enquiry. Demand Reactivation knows which paying clients have gone quiet.

The problem. Inboxes are where leads, suppliers, support requests, and noise all pile up together. The owner reads everything because no junior staff can be trusted to filter. The lead that arrived at 9pm Friday gets answered Monday 11am, often by which point the operator has lost the job.

What runs. Claude reads every inbound email, classifies it (lead, supplier, support, internal, noise), drafts a reply where appropriate, and surfaces only the items that need an owner decision. Sales replies are drafted in the operator's voice. Support replies use a tone profile. Suppliers get routed.

Where the value flows. Sales: faster reply means more jobs converted. Operations: owner stops doing inbox triage. Data quality: every email becomes a CRM activity, attributable to a contact and a deal. Demand Reactivation: replies that go quiet become signals for the reactivation engine.

The problem. Operators have call recordings nobody listens to. The owner doesn't have hours per week to sit through 50 calls. Coaching staff means catching what they did wrong before the next call, not after a monthly review.

What runs. Every recorded call gets auto-tagged with the signals you'd otherwise need a call coach to extract. Booking intent, price objections, competitive mentions, urgency, frustration. Surfaced as a feed of high-priority calls to listen to, not the full hour-by-hour stack.

Where the value flows. Sales: high-intent calls surfaced for follow-up the same day. Marketing: source-by-source view of which channels produced bookable intent. Operations: coaching anchored in real calls, not opinion. Demand Reactivation: every quote-requested-but-no-show becomes a reactivation candidate.

The problem. Most agencies test 2 to 3 ad variants because writing them is slow and reviewing them is slower. Audiences get refined on a hunch. The owner doesn't know whether the underperforming ad is bad creative or wrong audience.

What runs. Claude drafts 8 to 12 ad variants per campaign brief in the brand voice. We test against narrow audiences, let Meta's optimiser do the heavy lift, then Claude analyses what won and proposes the next round. Audience definitions get adjusted with reasons, not guesses.

Where the value flows. Marketing: more variants tested per dollar, fewer dead ad sets. Sales: leads arrive with traceable creative provenance. Data quality: every ad result becomes a learning signal for the next round. Demand Reactivation: ad-sourced leads who didn't convert become reactivation candidates.

The problem. SEO is no longer a search-engine optimisation problem. ChatGPT, Perplexity, Google AI Overviews, and Claude now produce a material share of buyer research traffic. Most sites are built for the old algorithm. They get traffic from Google but not from the AI engines.

What runs. Claude writes the blog content. Schema.org JSON-LD on every page. Internal linking matrix maintained as the content grows. AEO Readiness Checker on this site grades any page for AI-engine citability. Citation-worthy passages structured so AI engines pull them as answers, not just summaries.

Where the value flows. Marketing: traffic from the AI engines, not just Google. Sales: AI-quoted Gibson becomes a credibility signal at the first sales call. Data quality: every visit attributed to source including AI-engine origin. Demand Reactivation: traffic that came in once and went cold becomes a re-engagement target.

The problem. SMS reactivation campaigns either send the same generic message to everyone (low conversion) or take a human to draft each one (doesn't scale). Personalisation has to be real, but also has to fit a 160-character envelope and stay ACMA-compliant.

What runs. Every SMS is drafted in the workspace voice, scored before send, rewritten if weak, blocked if unsafe. Replies route into bookings or back into the conversation. The decision engine selects between multiple proven sales frameworks per lead and measures which one actually produced lift across the tenant.

Where the value flows. Customer engagement: actual two-way conversation, not blast and pray. Sales: warm appointments in the calendar. Data quality: every reply updates the CRM. Marketing: framework lift measured per campaign so the engine learns what works.