Solutions
We begin with the problem, not the model. Every engagement is configured around legal sources, professional roles, decision rights and measurable outcomes.
Areas of work
These are starting points, not fixed software packages. A solution may combine several capabilities depending on the legal process and the systems already in place.
Find answers across case law, policies, opinions, contracts and internal precedents with citations, permissions and a route back to the original source.
Support the contract lifecycle from intake and first review to comparison, negotiation context, execution and obligation follow-through.
Move repetitive coordination and information work into governed workflows while preserving clear responsibility for consequential decisions.
Bring matter histories, evidence, deadlines, correspondence and team knowledge into a structured and searchable working environment.
Translate regulations and internal policies into mapped requirements, assigned actions and evidence that can be reviewed over time.
Research, prototype and engineer focused internal tools or customer-facing legal technology products around a validated legal need.
Our delivery model
We work with legal and operational stakeholders throughout. Technical performance alone does not define success.
Map the users, current process, sources, risk and target outcome.
Test the highest-value workflow with realistic legal material and professional feedback.
Define permissions, evidence, review points, escalation and audit requirements.
Integrate the system, measure performance and support adoption in real work.
Choose the right starting point
Build with LawDiktat
When the workflow or product needs a purpose-built legal AI system.
Configure THAO
When governed automation must connect tools, policies, approvals and actions.
Learn with Alpha AI
When lawyers and teams first need practical capability to use and shape AI well.
Questions, answered
Open a question to understand how LawDiktat approaches the work.
No. A useful starting point is the current workflow, the people involved, the recurring friction and the outcome you want to improve. We can structure the technical path together.
Yes. We can assess an existing product, knowledge system or automation layer and work on a focused capability rather than replacing the whole stack.
Data handling is designed around the engagement. Options may include controlled retrieval, role-based access, private infrastructure, local models and explicit retention boundaries.
It depends on source readiness, integrations and risk. We first define a bounded workflow and success criteria, then provide a realistic delivery plan rather than promising a generic timeline.