Software built and proven for legal platforms where confidentiality is not a feature, it is the product.
Matter and case management, document automation, e-discovery and AI-assisted contract review, built for privilege, retention and the accuracy standards a legal team will actually sign off.
What building for LegalTech actually requires.
Legal software carries a confidentiality obligation that is stricter than ordinary data protection. Privilege can be waived by an access-control mistake, and the consequence lands on the firm's client rather than on the vendor, which changes how access is designed and tested.
Documents are the primary object, not a file attached to a record. Versioning, comparison, redaction, retention and defensible deletion are core behaviour, and each one has a legal definition that a generic document store does not satisfy.
AI assistance raises the accuracy bar rather than lowering the workload. A summarised clause or an extracted obligation that is subtly wrong is worse than no assistance at all, so grounding and citation back to source text is a requirement, not a refinement.
Where it breaks without care.
Access control is tested at the role level but not at the matter level, so a user with a valid role reaches a matter they are ethically walled off from.
Retention and deletion are implemented as a soft flag, leaving privileged content recoverable long after a defensible-deletion obligation said it should be gone.
AI extraction and summarisation is shipped without citation back to the source clause, so a lawyer cannot verify an output without redoing the work manually.
Redaction is applied visually rather than removing the underlying text, which is the failure that leaks content when a document is copied or its text layer extracted.
How we deliver it.
Ethical walls and matter-level permissions enforced in the data layer and tested adversarially, with cross-matter access attempts in the automated suite.
Document lifecycle behaviour, versioning, comparison, retention and defensible deletion, tested against the legal definition rather than the storage behaviour.
Redaction verified at the content level, confirming the underlying text is genuinely removed rather than visually covered.
AI features grounded in the document set with citation to the source clause, so every extracted obligation is checkable in one click.
Audit logging that records who accessed which matter and document, sufficient to answer a privilege or disclosure question after the fact.
Industry focus areas.
Matter & case management
Document automation
E-discovery
Contract lifecycle
AI clause review
Billing & time capture
Evaluating a build partner?
A two-week scoping engagement covering architecture review, risk mapping specific to legal & legaltech, and a 90-day delivery plan across build and quality engineering. You keep the plan whether or not you continue with us.
LegalTech questions, answered.
What is different about building legal software?
Confidentiality is enforced at matter level, not just role level, and documents are first-class objects with legal definitions for versioning, retention and deletion. Both shape the data model from the first architecture decision.
Can AI be used safely for contract review?
As an assistant with citations, yes. Every extracted term or summary should link back to the source clause so a lawyer verifies in seconds. Ungrounded summarisation of legal text is not safe to rely on.
How do you handle privileged data in test environments?
Synthetic or fully de-identified document sets by default. Where production-like data is unavoidable, handling, access and destruction terms are agreed in writing before any work starts.
Built for LegalTech,proven before launch.
Senior engineers who know where this sector breaks, and the quality engineering to prove your build does not.