FinTech
Problem space
Fraud, risk scoring, document processing, compliance.
The AI angle
Real-time scoring, anomaly detection, KYC/document AI.
Where it runs
Usually cloud (AWS/GCP) for scale; sensitive data in private VPCs.
Industries
AI that fits how your industry actually works.
Different industries have different constraints — data privacy, latency, scale, regulation. We pick the right approach and the right place to run your models.
Healthcare / MedTech
Problem space
Patient-data privacy, clinical documentation, decision support.
The AI angle
RAG over clinical docs, de-identification, on-prem LLMs.
Where it runs
Frequently on-prem / private — data can't leave the building.
E-commerce / Retail
Problem space
Recommendations, search, demand forecasting, pricing.
The AI angle
Ranking and rec engines, semantic search, forecasting.
Where it runs
Cloud-native (Vertex AI / SageMaker) plus data pipelines.
Logistics & Supply Chain
Problem space
Routing, ETA prediction, ops knowledge, documentation chaos.
The AI angle
Predictive ETAs, RAG ops assistants, optimization.
Where it runs
Hybrid — cloud compute, private stores for sensitive ops data.
Manufacturing / IoT
Problem space
Quality control, predictive maintenance, edge constraints.
The AI angle
Computer-vision QC, anomaly detection on sensor data.
Where it runs
Edge / on-prem — latency-critical, often offline.
SaaS & Tech
Problem space
Adding AI features fast, controlling inference cost, scaling.
The AI angle
LLM features, RAG, cost optimization (cloud ↔ self-hosted).
Where it runs
Hybrid — the classic 'cloud API is too expensive at scale' story.
Don't see your industry?
The constraints rhyme more than they differ. Tell us your problem — we'll tell you straight whether and how AI helps.
Talk to us