Managed cloud
We design, deploy, and operate multi-region infrastructure across AWS, Azure, and GCP — with cost, security, and reliability engineered from day one.
See how it works
Cloud infrastructure & applied AI
Enterprise scale,
engineered with the
calm of a swan.
SmartSwan builds and operates the cloud infrastructure and AI systems that regulated enterprises depend on — private, resilient, and observed to the millisecond.
The systems your business runs on — built and run by us.
Applied AI
Private LLM deployments, retrieval systems, and automation agents — trained on your data, hosted in your environment, evaluated against your metrics.
See how it worksData platforms
Warehouses, lakes, and streaming pipelines that make company-wide data trustworthy — governed, versioned, and observable end-to-end.
See how it worksPlatform engineering
Internal developer platforms, CI/CD, and paved paths that let your engineers ship faster with fewer meetings and fewer footguns.
See how it worksSecurity & compliance
Zero Trust architecture, identity, and continuous compliance evidence for SOC 2, ISO 27001, HIPAA, and DPDP — ready for auditors on demand.
See how it worksDigital transformation
We modernize legacy stacks in place — decomposing monoliths, migrating workloads, and re-platforming teams so change ships without downtime.
See how it worksOutcomes we're accountable for.
Named engagements with clear scope, timelines, and success metrics — not open-ended consulting retainers.
01
Cloud migration & modernization
Move from on-prem or single-cloud sprawl to a right-sized, multi-region footprint. Typical outcome: 30–40% infrastructure cost reduction with better SLOs.
02
Private AI & RAG deployment
Stand up an internal LLM assistant with retrieval over your documents, tickets, and code — hosted privately, evaluated continuously, safe for regulated data.
03
FinOps & cost engineering
Instrument spend, kill idle resources, right-size fleets, and negotiate commitments — usually paying for itself inside a quarter.
04
Reliability & SRE uplift
Define SLOs, build error budgets, and stand up on-call practices that hold up under real load — not just during the review.
The quiet part of enterprise engineering, done right.
Senior by default
Every engagement is led by engineers with a decade or more in production — no bench, no bait-and-switch after the pitch.
Own the outcome
We measure success by your metrics — availability, latency, cost, adoption — and share dashboards, not slideware.
Transfer, don't lock in
We leave your team stronger. Runbooks, docs, and pairing are part of every project so knowledge stays with you.
Regulated by design
Security, privacy, and audit-readiness baked in from architecture to runbook — because retrofitting them later is expensive.
Chosen for correctness. Combined for velocity.
We pick tools by fit, not fashion. These are the ones our teams reach for most often.
Cloud & runtime
AWS
Azure
GCP
Kubernetes
Nomad
Cloudflare
Data & AI
PostgreSQL
Snowflake
Databricks
dbt
Kafka
PyTorch
vLLM
LangGraph
Observability & security
OpenTelemetry
Grafana
Datadog
Vault
Terraform
Cilium
Cloud infrastructure
A cloud footprint that behaves like one system.
Multi-region by design, cost-aware by default, and observable to the millisecond — so your team stops firefighting and starts shipping.
- Region-active-active with automated failover and traffic steering.
- Terraform-defined environments with reproducible, reviewable changes.
- Cost dashboards down to the service, team, and pull request.
- SLO tracking with real error budgets that inform release decisions.
Edge
CDN
WAF
DDoS
Region A
API
Workers
Cache
Region B
API
Workers
Cache
Data plane
Postgres
Kafka
Object store
p99 42ms
err 0.02%
healthy
AI solutions
AI that reasons over your data — safely.
Private LLM deployments, retrieval systems, and agents that connect to your tools. Hosted in your environment, evaluated on your ground truth, governed by your policy.
- Private inference on GPU or CPU — nothing leaves your VPC.
- Retrieval over documents, tickets, and code with source citations.
- Evaluation harnesses tied to accuracy, latency, and cost per query.
- Guardrails, redaction, and audit logs for regulated workloads.
SmartSwan · internal assistant
Ops
Which regions saw p99 spikes yesterday, and what changed?
Assistant
Region B saw p99 climb from 41ms to 118ms between 14:20–14:45 IST, correlated with deploy #4821 (cache client upgrade). Rolling back the client restored baseline within 4 minutes.
grafana.slo
deploys/4821
runbook.cache
latency 320ms
cost ₹0.14
in-VPC
0
Platform availability across active accounts
0
Cloud regions we operate workloads in
0
Enterprise engagements delivered
0
Average infrastructure cost reduction
Common questions.
How is SmartSwan different from a traditional systems integrator?
We take responsibility for outcomes, not staffing hours. Every engagement has named SLOs, and we run the systems we build so incentives stay aligned long after the initial delivery.
Can you work inside our existing cloud accounts?
Yes — that's our default. We operate under your identity provider, use your networking, and leave code, infrastructure, and documentation in your repositories.
Where is our data during AI deployments?
Inside your environment. Inference, retrieval, and evaluation all run in a VPC you control, with no data leaving for third-party model providers unless you explicitly opt in.
What does a typical engagement look like?
A short assessment, a fixed-scope pilot with clear success metrics, and then a rollout phase. Most first pilots land production value in six to ten weeks.
Do you support regulated industries?
Yes. We regularly work under HIPAA, SOC 2, ISO 27001, and India's DPDP framework, and we can produce the evidence trail auditors expect.
Contact
Tell us what you're building.
A senior engineer will get back to you within one business day — no discovery-call gauntlet.
- Reply within1 business day
- First response fromSenior engineer
- Preferred formatAsync, in writing