Generative AI that is
governed, grounded and business-first.
ARGenesis uses Generative AI to summarise, draft, converse and synthesise across complex information but always anchored in your data, controls and decisions. We design GenAI solutions that combine strong prompting, retrieval, tools and guardrails so that outputs are useful, auditable and aligned to real work.
RAG · Copilots · Tools · Safety
GenAI decision pipeline
1. Ground
Retrieve relevant documents, data and policies (RAG).
Policy-aligned
2. Generate
Use domain-tuned prompts and tools to produce outputs.
Policy-aligned
3. Check
Apply rules, constraints and optional human review.
Policy-aligned
4. Act
Update systems, drafts or workflows with full traceability.
Policy-aligned
Indicative only. We design GenAI flows to balance responsiveness with cost, governance and required review.
Generative AI that is
governed, grounded and business-first.
ARGenesis uses Generative AI to summarise, draft, converse and synthesise across complex information but always anchored in your data, controls and decisions. We design GenAI solutions that combine strong prompting, retrieval, tools and guardrails so that outputs are useful, auditable and aligned to real work.
RAG · Copilots · Tools · Safety
GenAI decision pipeline
1. Ground
Retrieve relevant documents, data and policies (RAG).
Policy-aligned
2. Generate
Use domain-tuned prompts and tools to produce outputs.
Policy-aligned
3. Check
Apply rules, constraints and optional human review.
Policy-aligned
4. Act
Update systems, drafts or workflows with full traceability.
Policy-aligned
Indicative only. We design GenAI flows to balance responsiveness with cost, governance and required review.
What is Generative AI?
Models that can draft, summarise, translate and reason in natural language.
Generative AI systems learn patterns from large text, code and multimodal datasets. When designed well, they can help people synthesise information, explore options and produce tailored content quickly. Our focus is on using these capabilities safely, grounding them in your own data and combining them with deterministic rules and analytics.
Where GenAI helps
- Drafting and reviewing narratives, emails and reports.
- Summarising long documents and evidence packs.
- Answering questions over policies, wordings and playbooks.
- Supporting complex workflows with copilots and assistants.
How ARGenesis uses GenAI
- Retrieval-augmented design (RAG) for factual grounding.
- Tool use for calculations, lookups and workflows.
- Clear prompting standards and patterns
- Safety, logging and approval steps where needed.
ARGenesis GenAI capabilities
GenAI patterns tuned for real-world decision-making.
We focus on reusable patterns not one-off demos. Copilots, RAG systems and GenAI workflows are designed so they can be monitored, iterated and extended as your organisation matures.
RAG & knowledge systems
• Document ingestion and chunking pipelines.
• Embeddings and indexing tuned to your domain.
• Search, Q&A and summarisation over your content.
GenAI copilots & assistants
• Task-focused assistants for key roles.
• Prompt flows, tools and guardrails.
• UX patterns for trust and control.
Document & narrative intelligence
• Multi-document comparison and synthesis.
• Key point extraction and red-flag spotting.
• Drafting narratives for committees and clients.
Structured outputs & tools
• GenAI that writes to schemas and templates.
• Calls into calculators, APIs and rule engines.
• Bridging free text with structured systems.
Evaluation & alignment
• Task-based evaluation and benchmarking.
• Human review loops and feedback capture.
• Monitoring for drift, bias and failures.
Ops, security & governance
• Access control and data minimisation.
• Prompt and output logging for audit.
• Policies for safe, explainable GenAI use.
Cross‑industry use cases
Practical GenAI applications we design with clients.
Insurance
• Underwriting and broker enquiry assistants.
• Claims summarisation and coverage support.
• Reserving, pricing and capital narrative support.
• Policy wording Q&A and comparison helpers.
Healthcare
• Wellbeing and mental health assistants (Serenigy-aligned).
• Clinical note summarisation and coding support.
• Operational and pathway communication helpers.
Retail & digital
• Customer service and CX copilots.
• Product and campaign content drafting.
• Insights and explanation over analytics outputs.
Education & public sector
- Student or citizen information assistants.
- Consultation and policy document summarisation.
- Grant, case and evidence review support.
Part of the ARGenesis technology framework
Generative AI sits alongside rules, ML, deep learning and agents.
We do not see GenAI in isolation. It is one layer in an AI decision stack that includes Classic AI & Rule Engines, Machine Learning, Deep Learning & Transformation, Gentic AI (Evolutionary), Agentic AI, Applied AI and Data Engineering & AI Ecosystems.
1. Classic AI & Rule Engines
3. Deep Learning & Transformation
5. Gentic AI (Evolutionary)
7. Applied AI (Industry)
Next steps
Considering Generative AI for a new or existing process?
We can help you identify where GenAI truly fits, what data and controls you need and how to design solutions that are efficient, explainable and maintainable.
Not ready for delivery yet? We also run awareness and strategy sessions for leadership, boards and technical teams.