Databases find sources
The database layer supports discovery and assessment of legislation, case law, and commentary, including currency, coverage, metadata, and applicable versions.
Different jobs require different tools
A lawyer preparing advice for a client may need to identify the governing rule, select relevant authorities, compare competing interpretations, apply a conclusion to the facts, and produce an editable document. That can look like one technology task, but it contains several jobs with different objectives and different tests of success. A legal database is primarily concerned with discovering and assessing source material. A legal-AI work platform becomes relevant when selected material must be turned into analysis, drafting, or another professional output. The useful distinction is therefore not between old and new technology. It is between the jobs being performed.
The first destination is source research. Searching legislation, case law, and commentary belongs in the database layer because the immediate objective is to locate potentially relevant legal material. Coverage, search precision, metadata, and access to the appropriate version of an authority matter at this stage. If a lawyer is considering whether a limitation-of-liability clause is valid and applicable, the first job is to find the rules, decisions, and commentary that could answer that question. A work platform should not be treated as an assumed replacement for identifying the relevant source universe.
Work platforms create outputs
Selected materials become structured analysis, editable drafting, revision, collaboration, and communication tailored to the client or assignment.
The handoff preserves judgment
A working packet carries forward the question, facts, chosen authorities, selection reasons, uncertainties, deliverable, and drafting constraints.
Legal selection and monitoring in the database layer
The second destination is legal selection. A search result is not suitable merely because it contains the lawyer's keywords. The lawyer must determine whether an authority is current, complete, applicable to the question, and sufficiently close to the facts or procedural setting. Jurisdiction, court level, date, legislative history, and the posture of a decision may all affect that judgment. Selection remains closely connected to the database layer, even though it requires professional reasoning. Its proper output is not a long results list, but a bounded set of materials that the lawyer is prepared to use in the next stage.
Legal monitoring also belongs predominantly in the database layer. Tracking amendments, new decisions, or additions to relevant commentary is a source-oriented task. Its immediate output may be an alert, an updated search, or a collection of new authorities rather than a client-ready document. Once the change must be compared with an earlier position, incorporated into internal guidance, or explained to a client, the objective changes. The work has moved from observing the source environment to applying selected information in a professional output. This is a practical boundary because one monitoring event may produce several different downstream assignments.
Analysis, comparison, and drafting across the boundary
Analysis and comparison sit at the boundary between the two layers. The database supplies the selected legislation, decisions, and commentary. The work platform supports the task of organising differences, relating authorities to the supplied facts, and developing a usable structure for legal reasoning. A lawyer might compare two interpretations of the same requirement, identify the premise behind each one, and frame the implications for the client's position. Success is no longer measured by the number of sources retrieved. It is measured by fidelity to the selected material, clarity of analysis, and fitness for the intended audience.
Drafting belongs clearly on the work-product side. This includes preparing a legal opinion, revising a clause, structuring a notice, or assembling an editable first version of a submission. The objective is no longer to discover material but to produce text responsive to an assignment. Collaboration and knowledge reuse also lead to this layer when approved precedents, colleagues' comments, and arguments from earlier matters must be incorporated into a version the team can revise. Client communication is another destination: conclusions must be selected, qualifications explained, and detail adjusted for the recipient rather than simply reproduced from the research record.
The working packet and buyer criteria
The handoff between the layers should be treated as an explicit working packet. It should contain the legal question, relevant facts, selected materials, the reason for their selection, the intended deliverable, and drafting constraints. For a client opinion, those constraints might identify the jurisdiction, reference date, audience, length, structure, and issues that need separate treatment. The packet should also preserve uncertainty, such as a split in authority, an unconfirmed fact, or a source whose application remains open. This prevents the transition between tools from stripping away the professional decisions made during research and selection.
Technology buyers should evaluate each job against its own criteria. For a database, ask what sources are covered, how precisely they can be found, and what evidence supports currency, completeness, and context. For a work platform, examine the drafting and review process, treatment of editable documents, and interoperability with Microsoft Word. Collaboration and governance should be assessed separately as well. A broad demonstration can conceal weaknesses by blending these dimensions together. A more informative test covers at least five destinations: source research, legal monitoring, comparative analysis, drafting, and communication or delivery to the client.
A combined-stack test across both layers
A combined-stack test can use an assignment about the validity and application of a limitation-of-liability clause. The team defines the question and reference date, searches for legislation and case law, selects the authorities, and records known limitations. It then uses those selected materials to compare interpretations, prepare an editable opinion, and produce a concise client explanation. Evaluators score source discovery separately from work-product production. They ask whether the right material could be located and whether the resulting text can be reviewed, corrected, and used in professional work. AI-assisted output is not automatically correct or final, so lawyer verification and professional judgment remain necessary.
Wisanna occupies the work-product side of this boundary. It is a private and secure legal-AI workspace built for lawyers and legal professional work. Its current public product surfaces include AI Chat, a Microsoft Word add-in, and Wisanna Draft for editable legal documents. These capabilities make it appropriate to evaluate Wisanna against analysis, drafting, revision, and editable-output tasks, rather than treating it as an implicit substitute for the database layer. A sound buying decision asks for separate evidence on source coverage, drafting and review workflow, Word interoperability, collaboration, and governance, then tests whether the database and work platform can support the complete assignment together.
Turn selected legal material into work product
Evaluate Wisanna for analysis, drafting, revision, and editable legal documents, including work performed through Microsoft Word.
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