Professional Services
Measure what every AI tool returns to the practice. Then govern it.
Consultants, lawyers, and accountants are using AI tools on client work — most without procurement approval. Olakai shows you every tool in use, what it’s returning per practitioner, and whether client data is leaving your environment.
Your practitioners are using AI on client engagements. Most of it you didn’t approve.
Associates at your firm are using Harvey, ChatGPT, and Copilot on client work. Consultants are using Perplexity to research client industries and AI to analyze client data. Senior practitioners are using tools that never went through procurement. The productivity gains are real — but so is the client confidentiality exposure.
When a client asks “what AI tools are you using on our matter?” most firms can’t give a complete answer. When your managing partner asks what AI is returning per billable hour, nobody has the data. And when a partner’s laptop is running AI tools that send client work product to an external cloud, your data governance policy just became theoretical. Olakai gives you the complete picture — and the infrastructure to back it up.
By the Numbers
Professional services firms report that more than 70% of AI tool usage by practitioners happens outside formally approved and managed applications — on client matters, with client data.
You can’t prove client confidentiality or ROI on tools you don’t know about.
Client data never leaves your environment.
Olakai deploys inside your cloud tenancy or on your own hardware — AWS, Azure, GCP, or on-premises. No client work product, no matter details, no AI interaction logs are processed outside your perimeter. For law firms, consulting firms, and accounting practices with strict client confidentiality obligations, this isn’t a product feature — it’s the prerequisite your clients would require if they thought to ask.
Two lenses, one platform
Olakai is one platform, one data model, one set of controls. Olakai Assistive and Olakai Agentic are the two lenses you use to look at it — they share data, share context, and share Kai. What you see in one lens is immediately visible in the other.
Olakai Assistive
Track every AI tool your practitioners are using — on client matters and internally. License utilization across every approved seat. Shadow AI tools on client engagements, surfaced and risk-classified. Time saved per practitioner per week. The data your COO and managing partner need to run a governed AI program.
Olakai Agentic
Measure AI coding tool ROI for the internal engineering and IT teams supporting the practice, and govern every AI agent running in your practice — document processing, due diligence automation, contract review pipelines. Token spend by provider and team, full audit trails for every agent execution, and documentation ready for client review or regulatory inquiry.
Olakai Assistive — License utilization
Stop paying for seats nobody uses. Start measuring what they return.
Olakai Assistive maps actual usage to every AI license you’re paying for — by practitioner, by practice group, by tool. See which seats are idle before the next renewal cycle. Identify which practitioners are getting ROI and which need enablement. And surface every shadow AI tool being used on client matters alongside the approved ones, in one view.
- Active vs. idle seats across every approved AI copilot — by practitioner and practice group
- Time saved per billable hour from AI-assisted research, drafting, and analysis
- Shadow AI tools on client matters surfaced and risk-classified alongside licensed tools
Olakai Assistive — Per-tool governance
Know exactly what each AI tool is doing on client work.
Click into any AI tool — Harvey, Copilot, ChatGPT, Perplexity — and see its risk classification, governance status, data exposure profile, and usage across the firm. Which practice groups are using it, what data it’s touching, whether it’s been reviewed for client confidentiality compliance. Governance controls sitting right next to usage analytics, in the same view.
- Per-tool risk classification: client data exposure, practice group usage, data sensitivity
- Licensed vs. shadow status, governance controls, and policy enforcement per tool
- Prompt quality scoring and data handling compliance across every practitioner interaction
The KPIs that matter in professional services
Every pillar gives you a different lens on AI performance. Here are the metrics Olakai actually measures — across every vendor, every practitioner, inside your own infrastructure.
Olakai Assistive
Olakai Agentic
Why Measurement Changes Everything
Guessing about practitioner AI usage isn’t a governance posture. Olakai shows you every tool on every client engagement — approved, shadow, and personal — so you can manage what’s actually happening rather than what you assume.
The risk isn’t that practitioners use AI on client work. The risk is that they do it with tools that send client data to an external cloud. Olakai enforces the boundary — client matter AI stays inside your perimeter.
Paying for 500 Copilot seats when 200 are active is a finance problem. Not knowing which 200 are delivering ROI is a strategy problem. Olakai solves both — utilization and outcome in one platform.
Ask your AI program a question. Get a reasoned answer.
Kai synthesizes every Olakai data source — tool usage, license utilization, agent logs, governance status — and answers in plain English. With the reasoning shown and the data behind every number.
- “Which AI tools are our practitioners using on active client matters, and which of those aren’t approved?”
- “What’s our license utilization across every AI copilot — how many seats are actually active this month?”
- “Which practice groups are getting the most value from AI tools per practitioner hour?”
Illustrative conversation on the right: pick a seat, ask, and watch Kai reason over the same data every Olakai dashboard uses.