Measurable Outcomes
Faster to insight:weeks, not months — curated data products and self-serve access.
30–60% lower AI TCO:right-sizing GPU vs cloud burst; storage tiering and cache design.
Governed by default:lineage, approvals, and audit trails baked into the pipeline.
Latency where it counts:place models and data near users/events; burst global when needed.
The Platform We Build
Lakehouse & Streaming:batch + real-time ingestion, quality checks, curated layers for reuse.
RAG & MLOps:retrieval-augmented generation, feature stores, CI/CD for models, evaluation.
On-Prem GPU + Cloud Burst:predictable steady-state on-prem; spike into cloud for training/seasonality.
Governance:data contracts, catalog, lineage, role-based access, privacy and retention.
Built for South Africa
POPIA & residency:keep sensitive data resident in SA; minimise cross-border egress.
Cost & power reality:design for predictable run-rate with DR you can actually test.
Hybrid by design:tie into your landing zones, hosting/on-prem, and identity guardrails.
What Runs Where
Cloud:global reach, serverless ETL, vector stores at scale, LLM services, burst training.
Hosted (SA):curated data products, BI, and steady inference with locality & predictable cost.
On-Prem:GPU inference for latency-critical or sensitive workloads; low-jitter pipelines.
Hybrid:unified identity, guardrails, monitoring, and FinOps across the estate.
High-Value Use Cases
Customer 360:unify signals for cross-sell, churn, and service quality.
Agent Assist / Knowledge:RAG on your corpus for faster, compliant responses.
Fraud & Risk:real-time features and anomaly detection with lineage.
Docs & Process:OCR + RAG for contracts, claims, onboarding, and QA.
How We Engage
Discovery (2–3 weeks):current estate & data audit, priority use-cases & ROI, residency & risk assessment, platform blueprint & phases.
Platform Build:ingest, lakehouse, catalog; MLOps/RAG toolchain; on-prem GPU + cloud burst; governance & controls.
Use-Case Sprints:thin-slice delivery; value tracked per sprint; model evaluation & drift watch; rollout & enablement.
Run & Improve:SLOs & on-call, FinOps for data/AI, quality & lineage checks, quarterly roadmap refresh.
Recent Wins Through Partner Collective
−55% inference cost:on-prem GPU for steady load; burst to cloud for spikes.
Weeks to value:RAG assistant on private corpus reduced handling time by 23%.
Audit-ready lineage:data contracts + catalog → fewer audit findings.
Low-latency insights:streaming telemetry to SA-hosted store; < 200ms dashboards.
FAQ
Do we need a specific AI stack?No. We work with your choices. The operating model and controls matter most.
How do you handle privacy?Data contracts, role-based access, masking, and residency controls from day one.
Can we start small?Yes. One use-case sprint on a thin platform slice — then scale.
Who runs it?Your team with our enablement, or we run it under SLA with monthly reviews.