Solutions
Six practices.
One delivery engine.
Every practice is staffed by certified senior engineers, powered by our accelerator library, and wired into one delivery methodology — so multi-workstream programs never lose the plot.
Cloud that pays
for itself
We design AWS landing zones and operating models that scale cleanly — then run continuous FinOps loops that have cut client cloud bills by 30–40% while improving reliability.
- Well-Architected reviews & remediation
- Multi-account landing zones
- FinOps: rightsizing, savings plans
- DR & multi-region resilience
AI that survives
contact with production
From RAG platforms indexing millions of documents to voice agents making 12,000 calls a day — we build LLM systems with the guardrails and observability that separate demos from dependable software.
- RAG & enterprise knowledge platforms
- Autonomous & voice agents
- Eval harnesses & guardrails
- Model routing across providers
Product squads that
ship like founders
Small senior teams — full-stack, iOS, Android — that take products from Figma to app store. Telemedicine platforms, gaming assistants, fintech apps: built fast, built to scale.
- React / Next.js web platforms
- Native iOS & Android + on-device ML
- Real-time video & computer vision
- API platforms & integration
Move everything.
Break nothing.
Our migration factory has moved monoliths, data centers, and mainframe workloads to AWS with zero-downtime cutovers — funded in part by AWS MAP dollars we unlock as an Advanced Tier partner.
- 7R assessment & wave planning
- Zero-downtime cutover playbooks
- Monolith → microservices
- AWS MAP funding support
From data swamp
to decision engine
Lakehouses on S3 and Iceberg, streaming with Kafka and Kinesis, ML pipelines with SageMaker — we build the data foundations that make AI initiatives actually work.
- Cloud data lakes & lakehouse architecture
- Streaming & real-time pipelines
- MLOps: feature stores, monitoring
- BI modernization
Security that ships
with sprint one
Zero-trust network design, automated compliance evidence, and AI-workload threat modelling — security engineered into the platform, not bolted on before the audit.
- Zero-trust & identity-first architecture
- Built toward industry security best practices
- LLM security: prompt-injection defense
- Continuous posture monitoring
Build alone, or
ship with Mirai.
In-house hiring
3–6 months to hire a senior cloud/AI team. High fixed cost, slow ramp, single point of failure.
Generic agency
Broad but shallow — junior benches, no AWS-certified depth, no reusable accelerator IP.
Mirai Labs
Senior AWS-certified squads, live in weeks, backed by 80+ delivered accelerators. Scale up or down per sprint.
Most transformations touch three or four practices. Bring us the business problem — we'll assemble the right cross-practice squad and a roadmap in two weeks.
Yes — most enterprise engagements run 2-3 practices concurrently under one delivery lead, e.g. a migration paired with a new data platform.
Yes, alongside dedicated squads. Fixed-scope suits well-defined migrations or MVP builds; dedicated squads suit ongoing platform ownership.
Bring us the problem.
We'll bring the roadmap.