Legal RAG
Help users find relevant legal materials and work with answers linked to their sources. Legal documents require attention to structure, terminology and validity over time—areas central to our recent AI work.
Explore legal RAG
AI Solutions
Put your information to work.
Find relevant knowledge, answer complex questions and help people work across your business systems. We design and develop AI solutions around your information, your users and the tasks they need to complete.
Our strongest current specialisation is legal RAG. We bring that experience, together with software engineering expertise since 2003, to broader enterprise knowledge and assistant projects.
Where AI can help
Start with the task people need to accomplish.
Enterprise knowledge
Make policies, procedures, technical documentation and other internal knowledge easier to find and use. Retrieval-augmented generation (RAG) combines information retrieved from selected sources with an AI-generated answer. Source references help users check the underlying material.
Explore enterprise knowledgeIntelligent assistants
Give employees or customers a focused way to ask questions and complete defined tasks. An assistant can combine relevant knowledge with access to business applications, within agreed permissions and responsibilities.
Explore intelligent assistantsWorkflow automation
Support recurring tasks such as classifying requests, extracting information or preparing a response for review. Connect AI assistance to the surrounding process, with approval steps and clear routes for exceptions.
Explore workflow automation
Choosing an approach
Build what your situation requires.
An existing tool may already meet the need. Custom development becomes useful when your information, permissions, integrations or user experience require a closer fit. A combination of established tools and purpose-built components may be the right approach.
We assess these options against the business task, available data and operating constraints. Where feasibility is uncertain, a focused prototype can test the key assumptions before you commit to a larger implementation.
Consulting and solution architecture
From assessment to operation
Connect AI capability with software delivery.
Understand and design
Define the users, tasks and success criteria. Review the information sources, access rules and existing systems, then establish the architecture and project scope.
Prototype and evaluate
Test representative questions and tasks using relevant data. Assess answer quality, source support, failure cases, response time and expected operating cost.
Integrate and deploy
Connect the solution to your applications and identity systems. We support cloud and on-premises deployment across mainstream platforms, with the environment chosen around your requirements.
Support and improve
Plan monitoring, updates and ongoing evaluation as information and user needs change. Support scope, availability and response commitments are agreed for each customer.
Designed for everyday use
Define the controls alongside the capability.
Information and access
Identify which sources the solution may use, who may access them and how updates reach the system. Account for sensitive information and data boundaries in the architecture.
Quality and oversight
Agree how answers and actions will be evaluated, when human review is needed and what should happen when evidence is insufficient. Source-linked answers still need appropriate verification.
Performance and operation
Balance response time and operating cost against the task. Define monitoring, failure handling and maintenance responsibilities before the solution enters routine use.
Selected experience
Legal AI, built on software engineering experience.
Hungarian Legal Information Portal AI Search(Magyar Jogi Információs Portál MI Kereső)
iCode was the lead developer and solution architect for this AI search solution for Hungarian legal information. It supports natural-language questions and answers linked to source materials, with attention to the validity of legal information over time.
This is one example from our wider project history since 2003. It illustrates our experience connecting document processing, retrieval and AI answers within a software solution.
Read about the AI search project
Your next step
Which task would you like to make easier?
Tell us who needs help, what information they use and which systems are involved. We can help assess the opportunity and define a practical starting point.
Discuss your AI project