How to automate

AI Automation for Professional Services

Professional services firms sell time, but most of that time leaks into non-billable work — proposals, scoping, internal admin, document review, time tracking. Here's where AI gives you back hours each week, per professional.

Common challenges

Proposals taking 8-15 hours to assemble

Time tracking forgotten or estimated retroactively

Client onboarding (NDA, master agreement, kickoff) taking weeks

Document review (contracts, due diligence) eating senior time

Internal knowledge scattered — past work hard to find

What can be automated

Proposal automation

Brief in → proposal out in 30 minutes. Pulls from past similar projects, your standard pricing, your case studies. Sales/partner reviews and edits.

Time tracking AI

From calendar + email + Slack + git activity, auto-suggest time entries. Approve in batch, no more end-of-week guessing.

Client onboarding orchestration

From contract signature → KYC, MSA, payment setup, kickoff scheduled, materials prepared, all parallel. From weeks to days.

Document review (legal, due diligence)

Standard contracts checked in minutes against your firm's standards. Senior reviews flagged clauses only.

Knowledge base from past work

Semantic search across past project deliverables, client notes, internal memos. New consultant gets up to speed in days, not months.

Billing automation

Time entries → invoice draft → review → send → track. With dunning automation for late payments.

Common tools

Practice management: Clio (legal), Karbon (accounting), Productive (agency)Proposal: PandaDoc, Proposify, custom templatesTime tracking: Toggl, Harvest, customOpenAI / Claude for drafting + analysisCustom orchestration for firm-specific workflows

When to build custom

Most firms benefit from custom because workflows are firm-specific (your scoping logic, your billing rules, your knowledge structure). Off-the-shelf tools handle pieces but rarely the end-to-end.

Frequently asked questions

Will AI replace consultants/lawyers/accountants? +

No. AI removes administrative weight so professionals can focus on advisory work — where they bill the highest rates and add the most value.

Privilege/confidentiality concerns with client data? +

Critical. We use EU-hosted or on-premise models for any client data. Never send to consumer LLM services. Privilege requirements respected.

How much time does proposal automation save? +

Typical: 8-15 hours per proposal → 1-3 hours. For a partner billing $300/hr, ROI obvious within 5-10 proposals.

Can we trust AI on legal document review? +

For identification/flagging — yes, with 95%+ accuracy on standard contracts. Final advice stays with the lawyer. AI compresses the prep, not the judgment.

How does this fit our existing tech stack? +

We integrate with the major practice management systems and CRMs. For unique stacks, we build custom integrations.

Related case study /#/case/insolvency-notification-system →

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