AI Automations for Professional Services
Hundreds of CVs screened by hand against the same criteria every week.
AI automation replaces repetitive operational work — lead routing and qualification, follow-up sequences, data entry, reporting and content pipelines — with systems that run continuously and escalate to a human when judgement is required. For a professional services firm, the work is judged on a booked consultation with someone who can sign. Structured extraction and scoring against defined criteria, with every rejection reviewable by a person.
What is costing you money today
Hundreds of CVs screened by hand against the same criteria every week.
A site full of adjectives and no evidence, which loses to a competitor with three specific case studies and a named team.
What changes once this is in place
Structured extraction and scoring against defined criteria, with every rejection reviewable by a person.
How professional services actually buys
Two weeks to two months, decided on credibility and referral more than on price, with the website acting as the reference check.
- The unit of value
- a booked consultation with someone who can sign
- The common mistake
- A site full of adjectives and no evidence, which loses to a competitor with three specific case studies and a named team.
- What we do instead
- Publish the work, the method and the people. In this vertical the proof is the product.
What it has to talk to
A build for a professional services firm is mostly integration work. These are the systems we expect to exchange data with:
- CRM
- Calendar booking
- Proposal software
- Email sequences
The words your buyers actually use
Generic service copy loses to copy written in the vocabulary of the vertical. These are the terms that carry intent here, and the ones the pages we build are structured around:
- case studies
- our process
- book a consultation
- retainer vs project
- team credentials
The rules this sits under
Professional advertising rules vary by body — legal and accounting practices in particular have restrictions on solicitation and on claims of expertise.
What you get
- Process audit — The repetitive work in your operation, with volume and time cost attached, ranked by what automation is worth in each case.
- Automation design — Triggers, steps, decision points, escalation rules and failure handling — documented before anything is built.
- Build and integration — Implemented against your real systems — CRM, ERP, WhatsApp, store, spreadsheets — rather than in a demo environment.
- AI components where they help — Extraction, classification, summarisation and conversation, used where a rule genuinely cannot do the job. Rules are cheaper and more predictable where they can.
- Retrieval over your data — Grounding answers in your own documents and records, so responses are specific to your business rather than generic.
- Human-in-the-loop — Review queues for low-confidence decisions, with the interface for a person to correct and approve.
- Monitoring and logging — Every run recorded, failures alerted, and a dashboard showing what the automations did this week.
- Documentation and training — How each automation works, how to pause it, and what to do when it misbehaves — written for your team.