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Knowledge is scattered
Critical knowledge is distributed across documents, databases and people, so no single system holds a complete picture of the domain.
We provide consulting and engineering services for knowledge platforms, RAG and GraphRAG, AI agents and custom intelligent applications. Our specialists connect data, domain knowledge and software so organisations can search, reason and act with greater confidence.
Sources
Knowledge foundation
Ontologies, entities, relationships, business rules and retrieval structure.
Capabilities
Specialist consulting and engineering for organisations with complex data, specialised knowledge and high-value workflows.
Most difficulties we see are not model problems. They are knowledge, retrieval and accountability problems.
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Critical knowledge is distributed across documents, databases and people, so no single system holds a complete picture of the domain.
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Conventional search misses relationships, internal terminology and business rules, returning documents rather than usable answers.
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AI systems become risky when answers and actions cannot be traced, evaluated or controlled by the organisation that depends on them.
Identify practical opportunities, assess readiness and define an architecture and roadmap you can act on.
DetailsDefine a shared, machine-readable model of your domain using taxonomies, ontologies and controlled vocabularies.
DetailsDesign and implement client-owned knowledge graphs that connect data, content and business context.
DetailsGround language models in approved organisational information, with citations and measurable answer quality.
DetailsCombine document retrieval with entities and relationships where connected context genuinely adds value.
DetailsDesign agents that perform bounded tasks using approved data, tools and business rules, with human oversight.
DetailsTwelve service areas are described in full on the services page.
We work at the intersection of knowledge representation, retrieval and software engineering. That combination is deliberate: it is where most knowledge-intensive AI work succeeds or fails.
More about how we operateIllustrative use cases, described so you can recognise whether your own problem is a similar shape.
Answer internal questions from approved sources, with citations back to the original material.
Locate the obligations, definitions and exceptions that apply to a specific situation.
Standardise attributes and relationships across product and content records.
Retrieve precise passages from specifications, manuals and engineering documentation.
Assemble and compare findings across large bodies of literature or internal reports.
Support agents with consistent, source-linked answers drawn from current material.
Complete bounded, rule-governed tasks with human approval at consequential steps.
Explore relationships across systems that separate databases cannot reveal alone.
Define the business problem, users, sources and expected outcome.
Structure the domain knowledge, relationships, rules and retrieval requirements.
Implement the data pipelines, knowledge layer, AI components and user-facing software.
Evaluate quality, deploy responsibly and improve the system using real feedback.
These are engagement formats rather than fixed packages. Scope is agreed for each client.
Strategy, assessment, architecture and roadmap work for teams deciding where and how to start.
Validate one use case with a focused technical prototype before committing to a full build.
Design and deliver a complete client-owned solution, with documentation and handover.
Maintain, evaluate and extend deployed systems as data, usage and requirements change.
Practices we apply as standard. They describe our engineering approach, not a formal compliance or certification claim.
Answers and actions can be traced back to the material they came from.
Retrieval and agent behaviour respect existing permissions and data boundaries.
Decisions with real impact keep a person in the approval path.
Quality is measured against defined tasks rather than assumed from demonstrations.
Models, vocabularies and content have owners, versions and review paths.
Components are chosen so they can be replaced as needs and tooling change.
ABC Company brings together AI engineering, knowledge architecture, software development and delivery expertise through a small distributed team and specialist consulting relationships.
AI Engineering Lead
Hasan leads the technical design and engineering of AI solutions at ABC Company. His work covers machine learning, RAG and GraphRAG architectures, agentic workflows and the development of production-ready AI applications.
Master’s degree in Artificial Intelligence.
Principal Consultant — Knowledge & Agentic AI
External consultant
Anees is an external principal consultant specialising in knowledge graphs, ontologies, semantic architecture and agentic AI. He holds a PhD in Artificial Intelligence and brings extensive experience designing enterprise knowledge and trustworthy AI systems.
Engaged as an external consultant. He is not an employee, founder, owner, director or officer of ABC Company.
Head of Delivery & Operations
Mehdi coordinates project delivery, internal operations and communication across ABC Company’s distributed team. He helps ensure that engagements remain organised, transparent and aligned with agreed priorities.
The four profiles below are placeholders. Names, roles and images will be replaced once individual details are confirmed.
Senior Full-Stack Engineer
Builds the client-facing applications and services that sit on top of the knowledge layer. Placeholder biography.
AI/ML Engineer
Works on retrieval components, model integration and evaluation. Placeholder biography.
Data & Knowledge Engineer
Prepares data sources and implements graph and vocabulary structures. Placeholder biography.
Software Engineer
Supports application development, integrations and testing. Placeholder biography.
Tell us about the workflow, knowledge or data problem you are trying to solve. We can help assess the opportunity and identify an appropriate technical approach.
Discuss your project