Examples include law firms, accounting firms, consulting firms, advisory firms, tax professionals, engineering services, IT consulting, and managed professional services. The terminology changes, but the need for client and project effort data is similar.
Why Manual Time Entry Fails
Common problems include late entry, missing short tasks, wrong project, vague notes, timer fatigue, end-of-week reconstruction, and incomplete non-billable data.
Work Sources
AI-assisted capture can use activity from email, calendar, meetings, documents, browser, collaboration platforms, and project systems. The final entry should remain reviewable.
Project and Matter Attribution
Legal teams use matters. Consultants may use projects, engagements, workstreams, client codes, or phases. The same attribution problem exists across professional services.
Billable and Non-Billable Work
Classify work using the engagement's billing arrangement, not simply whether it involved a client. Keep the categories clear enough for users to review.
Work category | What the time record should distinguish |
Client-billable work | Work eligible for time-based billing under the engagement terms. |
Fixed-fee work | Client effort included in an agreed fee; still relevant to cost and staffing. |
No-charge effort | Client-related work recorded without a charge. |
Internal work | Administration and other firm responsibilities, separate from client delivery. |
Business development and training | Non-billable effort that still consumes team capacity. |
The final classification should reflect the firm's definitions and client requirements.
Narrative and Work Description
Clear descriptions help invoice review, project management, client transparency, and internal analysis. AI can draft descriptions from context, but users should confirm them.
Time-Based vs Fixed-Fee Work
Time data remains useful whether a client pays for hours or for an agreed outcome. The purpose of recording it changes with the fee arrangement.
Fee arrangement | How reviewed time data helps |
Time-based fees | Supports the work description, duration, and billing review. |
Fixed fees | Helps assess delivery cost, effective rate, staffing, and scope creep even when hours do not determine the invoice. |
Future engagements | Historical effort informs capacity and pricing assumptions under either model. |
Combine time with fee and cost data rather than treating hours alone as a profitability measure.
Project Economics
Combine time data with fees, internal cost, expenses, staffing, write-downs, and collections. Timekeeping is one input rather than the entire profitability system.
Privacy
Professional services teams should evaluate what data is collected, personal-activity exclusions, client confidentiality, retention, access, model training use, and subprocessors.
Integrations
A useful product should connect with the applications where work already happens and with the firm's billing or finance workflow. Verify exact current integrations before purchase.
Implementation
Start with a pilot group, clear project taxonomy, review rules, approved capture sources, billing-status definitions, success metrics, and structured user feedback.
How MIRA Fits
MIRA's current positioning includes law firms and professional services teams. It captures activity from connected work systems, supports AI-assisted entry preparation, and lets users review entries inside Microsoft Teams before release toward supported finance systems.
Frequently Asked Questions
Is AI timekeeping only for law firms?
No. Professional services teams that need project or client time data can use similar workflows.
Can AI timekeeping support fixed-fee work?
Yes, for internal effort, costing, staffing, and pricing analysis.
Should AI-generated entries be reviewed?
Yes. Users should confirm project, duration, description, and billing treatment.
Does MIRA support professional services?
MIRA's current product positioning explicitly includes professional services teams.
