Solutions
Private AI, cloud and platform engineering. One accountable partner.
Start from the problem you're facing — we bring the architecture, the team and the domain experience to solve it.
01 — AI & Data Systems Integration
Put AI to work on your own data — inside your perimeter.
The challenge: knowledge is scattered across CRMs, documents and internal systems; public AI tools can't be trusted with it.
- Enterprise RAG & vector search
- Custom AI agents & automated workflows
- On-premise & private AI setup
enterprise-rag-pipeline
CRM · ERP · DocsIngest & PII maskVector store
RetrievePrivate LLMGuardrailsAnswer + sources
data stays in perimeter
role-based retrieval
audit log per answer
02 — Secure Enterprise Platforms
Scalable systems for domains where data is sensitive by default.
The challenge: growth, compliance and security pull in different directions — and a breach costs more than any feature earns.
- High-load web & mobile architecture
- Healthcare & ID-protection compliance (GDPR / ISO 27001)
- B2B security & privacy infrastructure
DomainHealthcare
DomainSecurity
DomainHRTech
DomainRetail
Typical outcomeAudit findings fixed, ISO 27001 audit and certification passed.
03 — Cloud Infrastructure & Modernization
Scale without the cloud bill scaling faster.
The challenge: slow queries, fragile deployments and rising infrastructure costs as load grows.
- GCP / AWS architecture & migration
- High-performance database tuning
- Event-driven systems (CQRS / MQ)
Symptom → what we change
- Queries slow down as data grows
- Query plans, indexes, read replicas and caching
- Every release is a risk
- Automated CI/CD and repeatable environments
- Traffic peaks take the system down
- Queues, async processing and horizontal scaling
- The cloud bill grows faster than usage
- Right-sized resources, autoscaling and cost visibility per service
04 — From Legacy Systems to AI-Powered Products
Modernize what already earns money — without stopping it.
The challenge: a monolith that works but blocks every new feature, integration and AI initiative.
- Monolith → microservices refactoring
- Codebase audit & technical-debt removal
- AI capabilities layered on legacy tech
- STEP 1Audit & risk map
- STEP 2Strangler-fig extraction of services
- STEP 3Event bus & clean data layer
- STEP 4AI features on top
05 — Products from Idea to Production
One partner from first sketch to scaled launch.
The challenge: a complex product idea and no in-house CTO to make the architecture calls that matter later.
- Product architecture & design
- MVP → scalable enterprise launch
- Full-lifecycle DevOps & support
WK 0–2Discovery
WK 2–4Architecture
FROM WK 4MVP
ONGOINGScale