Solutions
Delivery
Find the bleed. Automate it. Ship it.
Delivery is how we run The Production AI Lifecycle inside your organisation — observe pain, architect the platform, engineer it, operate and evolve. Not slides. Not dependency.
Full methodology →How we work
Observe & Diagnose
We don't gather requirements — we observe how you really work and diagnose where time, money and risk accumulate.
Architect & Engineer
Platforms, not apps. IaC, GitOps, APIs, AI, MCP, RAG — built to run, not to demo.
Validate & Launch
Security, performance, cost, AI evals, reliability — then deploy with runbooks and rollback.
Operate & Evolve
SLOs, LLMOps, incidents, optimization — monthly evolution. The cycle restarts at Observe.
Operational hotspots
We study your company department by department. These are the patterns we hunt — where enterprises bleed hours and budget.
Operations & Finance
highSymptom
Spreadsheet reconciliations, copy-paste between ERPs, manual reporting
Cost
Senior people doing data janitor work
Our fix
Python ETL, event-driven pipelines, Elastic observability on business KPIs
IT & Engineering
criticalSymptom
Manual deploys, snowflake servers, tribal knowledge in Slack
Cost
Weeks to ship what should take hours
Our fix
Docker, AWS/Azure, Terraform, GitOps golden paths
Data & Analytics
highSymptom
Fragile batch jobs, no lineage, dashboards nobody trusts
Cost
Decisions made on stale or broken data
Our fix
Modern data stack, orchestration, quality gates, self-serve APIs
Product & AI teams
criticalSymptom
Notebook prototypes, no evals, no cost controls in production
Cost
AI demos that never survive compliance or scale
Our fix
LLMOps, RAG pipelines, gateways, production observability
Security & Compliance
mediumSymptom
Ad-hoc audits, secrets in repos, no asset inventory
Cost
Blockers discovered too late in the cycle
Our fix
Zero-trust patterns, automated policy checks, audit trails
Customer-facing teams
mediumSymptom
Manual ticket routing, repetitive support macros, no integration
Cost
Engineers pulled into ops instead of building
Our fix
Workflow automation, CRM/ITSM integration, intelligent routing
5-week engagement
Predictable. Transparent. Low risk. Every engagement starts here.
Week 1 · Observe
Enterprise observation
Interviews, architecture inventory, processes, shadow IT, spreadsheets, AI usage, cloud and security — Current State Report.
Week 2 · Diagnose
Engineering diagnosis
Bottlenecks, manual work, duplicated data, hidden costs, risks and AI opportunities — quantified per department.
Week 3 · Architect
Reference architecture
Target platform: cloud, security, AI, integrations, data, observability, governance — not a slide, a blueprint.
Week 4 · Engineer
Build plan & quick wins
IaC, CI/CD, APIs, ETL, automation roadmap — working pipelines before the long programme.
Week 5 · Validate
Readiness & handover
Production readiness check, runbooks, training, launch plan — your team owns what we built.
The Production AI Lifecycle
Not a project. A cycle.
Every engagement starts with an Architecture Review.
90 minutes. Written report. No surprises.
Request an Architecture Review