Legal Technology

Technology strategy and selection

Vendor-neutral selection of practice management, DMS, CLM, CRM and billing against your real requirements.

• Write requirements from how you actually work, not from a vendor’s feature list.
• Shortlist and score, with the same scenarios demonstrated by every vendor.
• Say plainly where a cheaper tool, or no new tool at all, is the right answer.

The result

A decision you can defend to the partners, with the reasoning written down.

System implementation and integration

Configuration, data migration and the integrations that stop double entry, with training, and a cycle time you can compare against the one we measured first.

• Configure the system around the agreed process, not around the demo.
• Migrate the data that matters and leave the rest in the archive.
• Connect the systems that hold the same data, so nobody retypes it.

The result

A system people use, and a number that shows they use it.

AI strategy and governance

An AI policy that fits your duty of confidentiality, company accounts with an audit trail, and human review rules.

• Decide what may be put into which tool, in one page people will actually read.
• Move AI use off private accounts onto company accounts with an audit trail.
• Set the review rules: what a human checks, when, and what gets recorded.

The result

AI use that is visible, allowed, and defensible to a client or a regulator.

Automation and AI adoption

From document assembly to research assistants, sequenced by impact and measured against a baseline.

• Pick the tasks that repeat often enough to be worth automating, and measure them first.
• Build the smallest version that works, with the people who do the task.
• Compare against the baseline, keep what pays and drop what does not.

The result

Fewer hours on work nobody should do by hand, with the saving measured.