The best AI timekeeping software for a law firm is the product that fits its work sources, lawyer-review routine, billing system, privacy requirements, and implementation capacity. Start with those requirements, then test a shortlist using representative matters and a defined pilot.
This guide compares MIRA, Laurel, Billables AI, Intapp Time, PointOne, and Ajax. It is published by MIRA and summarizes public vendor materials checked October 15, 2026. It is not an independent benchmark, an exhaustive market ranking, or a claim that every listed capability is available in every configuration.
What Should Law Firms Look for in AI Timekeeping Software?
A useful evaluation should go beyond whether a product can generate a timesheet. Law firms should consider the full path from work activity to an approved billing entry.
Important criteria include:
Area | Questions and checks |
Capture and assignment | Automatic capture of relevant work activity; Matter and client association |
Narratives and coding | Drafting of clear billing narratives; Support for task and activity codes |
Client rules and review | Client billing guideline controls; Lawyer review before release |
Systems fit | Integration with billing and finance systems; Fit with Microsoft 365 and document systems |
Trust and rollout | Privacy and security controls; Implementation effort and user adoption |
The strongest platform for one firm may not be the strongest platform for another. A large global firm with an established Intapp environment may evaluate timekeeping differently from a 50-lawyer Microsoft 365 firm looking for a faster deployment.
AI Legal Timekeeping Software Comparison
Use a consistent workflow comparison. An item not described on a public webpage should be confirmed with the vendor, rather than treated as an absent feature.
Platform | Publicly documented focus | Demonstration to request |
Activity capture and draft entries, with review in Teams and Outlook and supported billing connections | Review a working day and reconcile the approved time with the billing destination | |
Automatic work collection, compliance review, and work intelligence | Demonstrate the firm's source coverage and review workflow | |
Background activity reports, matter matching, and narrative generation | Correct a matter and narrative using representative work | |
Automated capture, timers/direct entry, and compliance workflows | Demonstrate configuration and administration within the proposed environment | |
AI timekeeping, retrospective capture, and AI-assisted timers | Test interrupted work and transfer to the actual billing system | |
Capture, draft narratives, review, and billing release | Demonstrate lawyer corrections, client-rule handling, and accepted release |
Price comparisons should identify the applicable plan and commitment. MIRA's pricing page displays MIRA at $39 per user/month with annual billing and MIRA+ at $69; MIRA+ lists AI narrative drafting, delegation, and OCG features. The monthly-billing rates shown are $59 and $99 respectively. Confirm current terms and obtain comparable written proposals from other vendors. Unavailable public pricing is not evidence that a product is more expensive.
MIRA: Microsoft 365 Native Review and Release
MIRA is designed around reducing the amount of manual reconstruction required from lawyers while keeping the lawyer in control of what becomes a time entry.
MIRA can detect activities from digital work such as emails, meetings, documents, websites, and local files. AI then helps categorize the activity and prepare structured entries and billing narratives. Lawyers can review and edit captured time before releasing it to a connected billing system.
A major workflow distinction is MIRA's placement inside Microsoft Teams and Outlook. Firms whose lawyers already spend most of the day in Microsoft 365 can review time without introducing another daily destination.
MIRA also supports integrations with legal and finance systems including Aderant and Elite, while MIRAlink is positioned as a way to extend connections to additional systems.
MIRA may be especially relevant for firms that value:
Microsoft Teams and Outlook workflow
Fast deployment with limited IT overhead
Lawyer-controlled review before release
AI-assisted narratives and coding
Integration with existing billing infrastructure
Laurel: Broad Automated Work Capture
Laurel positions its platform around automated work capture, revenue recovery, compliance review, and work-time intelligence.
Its current legal offering describes automatic collection of chargeable and non-chargeable digital activities, including email, calendar, documents, web activity, and offline work. Laurel also supports controls around narratives, entry validation, and matter access.
Laurel may be attractive to firms looking for a mature passive capture model across a broad set of applications and legal systems.
Firms evaluating Laurel should review which applications need to be monitored, how attorney privacy controls are configured, how captured activity becomes an approved time entry, and how the platform connects to the firm's billing environment.
Billables AI: Automated Capture and Narrative Generation
Billables AI focuses on automated legal time tracking and AI-generated time entries.
Its current product materials describe background capture of work activity and generation of entries containing clients, matters, and narrative descriptions. The platform also supports client billing guidelines and promotes cross-device activity capture.
Billables AI may appeal to firms that want an AI-first timekeeping experience focused on reducing the administrative effort required to reconstruct work and write narratives.
During evaluation, firms should test matter matching, narrative accuracy, privacy controls, billing-system integration, and the amount of attorney review required before time can be submitted.
Intapp Time: Enterprise Timekeeping and Compliance
Intapp Time combines time capture with a strong compliance focus.
Intapp describes automated capture, timers, direct entry, mobile timekeeping, AI-powered data capture, compliant-language prompts, reporting, and integration with client requirements. In 2026, Intapp also expanded AI capabilities including work-code prediction and narrative compliance.
Intapp Time can be a natural candidate for larger firms already using Intapp products for compliance, client terms, or other legal operations.
Firms considering Intapp should evaluate the advantages of the broader platform against implementation scope, architecture, administrative requirements, and the firm's existing systems.
How to Run a Useful 30-Day Timekeeping Pilot
A pilot should measure more than whether lawyers like the interface.
Choose a representative group of timekeepers and measure:
How much activity is surfaced that would otherwise require manual reconstruction.
How accurately the software assigns clients and matters.
How much editing AI-generated narratives require.
Whether the workflow follows client billing requirements.
How long lawyers spend reviewing time each day.
Whether entries reach billing earlier and with fewer corrections.
Whether the software works with the firm's existing DMS, Microsoft 365 environment, and finance systems.
Whether lawyers understand and trust the privacy controls.
The goal is to identify the system that improves time capture without creating a new administrative burden.
Which AI Legal Timekeeping Platform Is Best?
Choose from demonstrated fit, not the number of AI features advertised. For a Microsoft 365 firm, review placement may be decisive; for another firm, the billing connection, governance model, or support arrangement may carry more weight. Every shortlisted product should pass the same critical tests.
For a 50–200-lawyer firm, use the mid-sized-firm evaluation guide. Compare commercial scope with the cost guide, document requirements in the RFP checklist, and structure the decision using the partner pilot plan. Firms evaluating a change from Laurel can use the alternatives guide.
PointOne: AI Timekeeping and Flexible Entry
PointOne's product page describes automatic and retrospective time capture, AI-assisted timers, and billing-system connections. Include it when evaluating how capture and time-entry habits interact. Ask the same correction and transfer questions used for the other vendors, and assess daily effort with the firm's own users.
Ajax: Capture, Review, and Release
Ajax describes a capture-to-review-to-release workflow, generated narratives, and client-guideline support. Include representative client rules and an incorrect draft in the demonstration. Measure the human work needed to turn suggestions into accepted entries rather than assuming that generated text is ready to bill.
Frequently Asked Questions
What is AI legal timekeeping software?
AI legal timekeeping software uses work activity and contextual information to help lawyers create time entries with less manual reconstruction. Depending on the product, it may capture activity, associate work with matters, draft narratives, suggest billing codes, and support review before billing.
Can AI timekeeping replace lawyer review?
Law firms should retain human review. AI can help prepare entries, but lawyers remain responsible for confirming the matter, duration, description, confidentiality, and compliance with client billing requirements.
Does automatic time capture mean employee surveillance?
Not necessarily. Products use different capture methods and privacy models. Firms should review exactly what is collected, whether content or screenshots are captured, how long data is retained, who can access it, and what the lawyer can exclude or edit.
What integrations matter most for law firms?
Common requirements include Microsoft 365, Outlook, document management, practice management, time and billing, finance, identity, and client guideline systems. The right integration set depends on the firm's existing technology stack.
How should a law firm compare AI timekeeping vendors?
Use a pilot with real lawyers and real workflows. Measure capture completeness, matter matching, narrative quality, compliance, review time, integration, privacy, deployment effort, and adoption rather than relying only on feature lists.
