Put your data on rails
so every AI system stays trusted and live.
ARGenesis designs the data foundations, pipelines, models, quality and governance that keep Classic AI, ML, Deep Learning, GenAI and Agentic systems running safely in production across insurance, health, retail, education and public sector.
Data quality · Lineage · Governance
AI data pipeline snapshot
1. Ingest
Policy, claims, bordereaux, external feeds
SLA 99%
90%
2. Model
Curated lakehouse, feature store, document store
93%
3. Serve
APIs for ML, GenAI, reporting and agents
96%
4. Observe
Quality, drift, lineage and cost dashboards
99%
Example business output
One governed data layer feeds reserving, pricing, IFRS 17, GenAI assistants and MI dashboards cutting duplication, reconciliation effort and model risk.
What is Data Engineering & an AI Ecosystem?
The plumbing, structure and standards that keep AI useful and safe.
Data Engineering covers ingestion, modelling, transformation and serving of data into forms that AI and humans can reliably use. An AI ecosystem adds the governance, platforms, integrations and lifecycle management so that models, rule engines and agents work together instead of as isolated experiments.
Where we help
- Reducing reconciliation and manual data wrangling.
- Giving actuaries, analysts and data scientists trusted inputs.
- Enabling real‑time and batch AI side‑by‑side.
- Making compliance, audit and reporting simpler.
How we work
- Assess current data and AI landscape.
- Define target architecture and migration paths.
- Build incremental, value‑driven pipelines and hubs.
- Embed monitoring, governance and documentation.
ARGenesis capabilities
Data foundations designed for AI‑heavy, regulated organisations.
We combine actuarial and operational understanding with modern data engineering to design ecosystems that serve today’s reporting needs and tomorrow’s AI ambitions.
Ingestion & integration
• Batch and streaming pipelines.
• Policy, claims, finance and external sources.
• APIs, file drops, messaging and event buses.
Data modelling & lakehouse
• Domain‑driven data models (insurance, health, retail).
• Curated lakehouse and marts for AI and BI.
• Slowly‑changing dimensions and history tracking.
Feature and document stores
• Reusable ML and risk features.
• Vector stores for GenAI and search.
• Document hubs for contracts, bordereaux and reports.
Quality, lineage & metadata
• Data quality rules and scoring.
• Lineage from source to model and report.
• Business and technical metadata catalogues.
Ecosystem integration
• Connect to GenieAPP, GenieLab and GenieUs.
• Expose governed APIs to internal teams.
• Plug into existing BI, actuarial and finance tools.
Operations & DevOps / MLOps
• Environments, CI/CD and deployment pipelines.
• Monitoring, alerting and cost observability.
• Access control, security and compliance support.
Cross‑industry use cases
One ecosystem, many AI and analytics workloads.
Insurance
• Single source of truth for pricing and reserving.
• Shared data and features across lines and entities.
• IFRS 17, regulatory and MI from the same layer.
• Data backbone for GenieAPP and GenAI co-pilots.
Healthcare
• Unified view of patients, episodes and outcomes.
• Pipelines feeding triage, risk and capacity models.
• Evidence base for quality and commissioning.
Retail & digital
• Click‑stream, transaction and product data hub.
• Feature store for recommendation and CLV models.
• Real‑time and batch analytics from one fabric.
Education & public sector
• Integrated view of learners, citizens and services.
• Pipelines for demand, vulnerability and outcome models.
• Transparency and auditability for public reporting.
Part of the ARGenesis technology framework
Data Engineering is the substrate for everything else.
Classic AI, Machine Learning, Deep Learning, GenAI and Agentic AI all rely on robust data foundations. Our AI ecosystems make sure those foundations are shared, governed and ready for the next wave of innovation.
1. Classic AI & Rule Engines
3. Deep Learning & Transformation
5. Gentic AI (Evolutionary)
7. Applied AI (Industry)
Next steps
Need to rationalise data and unlock AI at the same time?
We can help you design a pragmatic AI ecosystem roadmap from quick‑win pipelines to strategic platforms aligned to regulatory, actuarial and operational realities.