Sovereign Cloud & AI Platform
Your Cloud. Your Data. Your Infrastructure.
Local Data. Independent Cloud. Managed Applications.
Locara provides locally operated cloud, AI and managed application infrastructure — helping organizations keep critical data within their required jurisdiction while gaining the capabilities of a modern cloud platform.
- Local data residency
- Cloud infrastructure
- AI ready
- Managed operations
- DevOps & SRE
- Enterprise support
Runs with the clouds and platforms you already use
- AWS
- Microsoft Azure
- Google Cloud
- AWS Outposts
- Azure Local
- Cloudflare
- DigitalOcean
- Hetzner
- Contabo
- OVHcloud
Trademarks belong to their respective owners. Shown to describe interoperability, not partnership.
The problem
Cloud shouldn’t mean losing control.
Data residency
Application and customer data may need to remain within a specific country or jurisdiction, and you need to be able to show that it does.
Cloud dependency
Deep dependence on one external provider’s managed services makes pricing, availability and exit somebody else’s decision.
Operational complexity
Kubernetes, databases, networking, monitoring, backups and security each demand specialist engineering that most teams cannot staff at once.
AI infrastructure
AI applications need GPU compute, model serving, retrieval and data pipelines — next to data that often cannot leave the building.
Skills and support
DevOps, SRE and application operations are needed continuously, not just during the project that created the platform.
Recovery
Backups exist almost everywhere. Tested recovery, with an agreed time to restore, is far rarer.
The Locara approach
Cloud experience. Local infrastructure. Managed end to end.
Cloud infrastructure
Compute, networking, storage, Kubernetes, managed databases and backup, delivered as a platform.
AI infrastructure
GPU compute, model hosting, inference and the data services AI applications depend on.
Managed operations
DevOps, CloudOps, SRE, monitoring, security and maintenance, with named engineers.
Application platform
Deploy and run applications without owning every layer of infrastructure underneath them.
How a workload is layered
Customer application
Your services and users
Locara application platform
Deploy, run, observe
Managed Kubernetes & compute
Clusters, VMs, autoscaling
Database, storage & messaging
PostgreSQL, object storage, cache
AI & GPU infrastructure
Model serving, inference, vectors
Locara operations
DevOps, SRE, incident response
Locally operated data centre
Compute, network, storage
Products
Three products, one platform
Locara Cloud
CloudCloud infrastructure, operated locally.
- Virtual machines
- Managed Kubernetes
- Autoscaling
- Private container registry
- Private networks
- Load balancing
- Network policy
- VPN & private interconnect
- Block storage
- +6 more
Locara AI
AIAI infrastructure for applications that need local data and local compute.
- GPU nodes
- Training & fine-tuning
- Inference serving
- LLM hosting
- Model gateway
- Private AI environments
- Vector database
- Document pipelines
- Object storage
- +3 more
Locara Managed
ManagedWe operate your cloud and applications — with you, or for you.
- CI/CD pipelines
- GitOps
- Infrastructure as Code
- Kubernetes operations
- Monitoring & alerting
- Incident response
- Patching & maintenance
- SLOs
- Capacity planning
- +4 more
How it runs
How workloads run on Locara
Managed Kubernetes on local infrastructure
A production cluster whose control plane, upgrades and observability are run by Locara engineers, with the workloads and their storage in the same locally operated facility.
- Web, API and background workloads scheduled across worker nodes; GPU nodes join the same cluster for AI services.
- Persistent volumes, S3-compatible object storage and backups next to the cluster rather than in another region.
- Metrics, logs and alerts watched by the team that operates the platform, with patching and upgrades handled for you.
An MLOps lifecycle that stays on your data
From governed data to a versioned model in production: training runs on local GPU capacity, and monitoring closes the loop by triggering retraining when a model drifts.
- Datasets and features held in local object storage and databases, so training data does not leave the jurisdiction.
- Training and evaluation as repeatable jobs on GPU nodes, with every model registered, versioned and traceable.
- Canary releases, then live monitoring of latency, drift and cost, with the team on call for the platform underneath.
LLM applications with retrieval, guardrails and evaluation
A retrieval-augmented pipeline over your own documents, served from local GPUs, with policy checks on the way in and out and evaluation gating every change.
- Your documents chunked, embedded and indexed in a vector database that lives with the rest of your data.
- A gateway for authentication and guardrails, retrieval and reranking, model inference on GPUs, and output policy checks.
- Traces and feedback feed evaluation sets, so prompt, model and index changes are scored before release.
Running a smaller site, store or SaaS?
There is a packaged version of this platform: high availability, TLS, a managed database, Redis, scheduled jobs and maintenance under an SLA — without a platform team of your own.
Data localization
Keep your data where it belongs.
Typical public-cloud path
Capable, global, and operated outside your jurisdiction.
Your users and applications
External cloud provider
Managed services under external control
Remote region
Chosen from available regions
Data stored and processed abroad
Regulatory and operational dependency to manage
The Locara path
The same capabilities, operated locally.
Your users and applications
Locara cloud platform
Kubernetes, databases, storage, AI services
Locally operated data centre
A facility you can identify
Data stays in your jurisdiction
Including backups, logs and AI workloads
Locara helps organizations design and operate infrastructure around their data residency and jurisdictional requirements. We do not claim that using the platform automatically satisfies any particular regulation — your legal and compliance teams define the requirement, and we build and evidence infrastructure that supports it.
Cloud independence
Reduce cloud dependency. Keep cloud capabilities.
- Infrastructure control
- Capacity, placement and configuration decided with you, not inherited from a default.
- Local operations and support
- Engineers who operate the platform, reachable under local arrangements.
- Open technologies
- Kubernetes, containers, PostgreSQL, S3-compatible storage and standard APIs.
- Infrastructure as code
- Environments defined in code, so they can be rebuilt — or taken elsewhere.
- Automation by default
- Provisioning, delivery and recovery automated rather than documented and hoped for.
- Portability
- Exit planned from the first design, because that is what makes independence real.
Managed application platform
Don’t just host your application. Let us operate it.
- 01
Build
Pipelines, container builds, infrastructure as code and environments.
- 02
Deploy
Automated, reviewable releases with rollback that has been tested.
- 03
Run
Kubernetes, databases, networking and capacity operated for you.
- 04
Monitor
Metrics, logs, traces and alerts tied to user impact.
- 05
Maintain
Patching, dependency upgrades, performance work and small fixes.
- 06
Improve
Reliability engineering, cost work and architecture reviews.
- CI/CD
- GitOps
- Container orchestration
- Observability
- Incident response
- Security operations
- Backup & DR
- Application maintenance
AI application hosting
Build AI applications without moving sensitive data.
AI application
Copilot, assistant, internal platform or API
- Enterprise copilots
- RAG systems
- Document intelligence
AI gateway
One entry point with authentication, quotas, routing and audit logging
- Access control
- Rate limits
- Prompt logging
Model serving
Open-weight LLMs and embedding models, versioned and monitored
- LLM hosting
- Inference
- Evaluation
GPU infrastructure
Scheduled accelerated compute with per-team quotas
- Training
- Fine-tuning
- Serving
Data services
Retrieval and storage under the application
- Vector database
- PostgreSQL
- Object storage
Local data
Documents and records that stay inside your jurisdiction
AI workloads can be designed around local data residency requirements, and many run well on local infrastructure. Some do not: where you need frontier-model capability or large bursty training, we will say so and help you design the boundary deliberately rather than claim everything belongs in one place.
Tools & technology
Open technology, operated properly
- Kubernetes
The orchestration layer under every containerised workload we run.
Containers & orchestration
- Docker
Container builds and local development parity.
Containers & orchestration
- Helm
Packaging and versioning for everything deployed to a cluster.
Containers & orchestration
- Proxmox VE
Virtualisation and clustering under the private cloud platform.
Virtualization & private cloud
- OpenStack
Private cloud infrastructure services at data-centre scale.
Virtualization & private cloud
- GitLab CI
Pipelines for build, test, scan and deploy.
CI/CD, GitOps & IaC
- GitHub Actions
Pipelines with OIDC to cloud accounts and no stored keys.
CI/CD, GitOps & IaC
- Jenkins
Long-standing pipelines we operate and modernise in place.
CI/CD, GitOps & IaC
- Argo CD
GitOps delivery: clusters reconcile what is committed to Git.
CI/CD, GitOps & IaC
- Terraform
Infrastructure as code for every environment we build.
CI/CD, GitOps & IaC
- Ansible
Configuration management and repeatable operational runbooks.
CI/CD, GitOps & IaC
- PostgreSQL
Managed relational database with point-in-time recovery.
Databases & streaming
- Percona XtraDB Cluster
Synchronous MySQL clustering for high-availability workloads.
Databases & streaming
- Redis
Caching, queues and session storage.
Databases & streaming
- Apache Kafka
Event streaming clusters for high-throughput pipelines.
Databases & streaming
- MinIO
S3-compatible object storage inside your own environment.
Storage
- Longhorn
Replicated block storage for Kubernetes, with snapshots and backup.
Storage
- Traefik
Ingress and routing with automatic certificate management.
Networking & ingress
- HAProxy
Load balancing and TLS termination at the edge of the platform.
Networking & ingress
- HashiCorp Vault
Secrets management and short-lived dynamic credentials.
Security & secrets
- Trivy
Vulnerability scanning for images, dependencies and IaC.
Security & secrets
- SonarQube
Static analysis and quality gates in the delivery pipeline.
Security & secrets
- Prometheus
Metrics collection and alerting rules across the platform.
Observability
- Grafana
Dashboards for platform and application health.
Observability
- NVIDIA GPU
Accelerated compute for training, fine-tuning and inference.
AI & data science
- Qdrant
Vector database for retrieval-augmented applications.
AI & data science
- LangGraph
Stateful agent and workflow orchestration for LLM applications.
AI & data science
- FastAPI
The service layer most AI applications are exposed through.
AI & data science
- MLflow
Experiment tracking and model registry.
AI & data science
- AWS
Integrated where a workload genuinely belongs in public cloud.
Cloud & hosting
- Microsoft Azure
Hybrid designs alongside locally operated infrastructure.
Cloud & hosting
- Google Cloud
Used selectively, usually for data and AI services.
Cloud & hosting
- Cloudflare
Edge protection, DNS and DDoS mitigation in front of the platform.
Cloud & hosting
Product names and logos are trademarks of their respective owners, shown to describe what the platform is built with. They do not imply endorsement or partnership. Some marks are shown as text where the owner restricts logo use.
Engineering services
Cloud & platform engineering
Platform Engineering
Paved roads so product teams ship without becoming infrastructure experts.
Solutions
Start from the outcome you need
Data Localization
Keep regulated and sensitive data inside the jurisdiction that requires it.
Application Hosting
Run business applications on infrastructure that someone is accountable for.
Cloud Modernization
Move from servers and scripts to containers, automation and defined environments.
AI Application Infrastructure
Serve models next to your own data, with the operational plumbing included.
Managed Kubernetes
Clusters that are built, upgraded, watched and recovered by people who do it daily.
Industries
Where control matters most
Technology Companies
Cloud-native infrastructure and AI platforms without building an ops team first.
Small Business & Professional Services
Business sites, CMS and portals that simply have to stay up.
Why Locara
Six reasons organizations choose a local platform
Local
Infrastructure designed around the data residency your organization has to meet.
Independent
Reduced dependency on external providers for the workloads where that matters.
Cloud-native
Kubernetes, containers, APIs and infrastructure as code — not a rebranded server rack.
AI-ready
GPU capacity and model serving built into the platform, not bolted on later.
Managed
DevOps, CloudOps, SRE and application operations delivered by named engineers.
Reliable
Monitoring, backup, tested recovery and operational support as standard.
Architecture
The platform, layer by layer
Layer 1 of 6
Experience
How teams interact with the platform: a portal for self-service, APIs for automation, and a CLI for engineers who live in a terminal.
- Portal
- API
- CLI
Coverage
Where we can run your platform
- Operating today
- Available on request
- Partner facility
- Planned
Available on request
Dhaka
Bangladesh
- Cloud infrastructure
- Managed Kubernetes
- AI / GPU
Locations marked “available on request” are places we can stand capacity up with our facility partners, subject to survey, contracts and lead time — they are not existing Locara capacity. Ask us for current status, lead times and the exact facility for any location that matters to you.
Trust
Built to be inspected
Local infrastructure
Workloads run in a facility we operate and can identify for you.
Security-focused architecture
Segmentation, least privilege, encryption and managed secrets by default.
Backup & disaster recovery
Per-workload objectives, encrypted copies and restore drills on a schedule.
Monitoring & observability
Metrics, logs and traces across platform and applications.
Least-privilege access
Named accounts, strong authentication and reviewed standing access.
Infrastructure as code
Environments reproducible from version control, with change history.
Kubernetes & open standards
Portable technology choices, so leaving stays an engineering task.
Audit trails
Administrative actions logged and retained for review.
The platform is designed to support security and compliance requirements, and we provide the technical evidence your auditors ask for. We do not claim certifications the company has not obtained — ask us directly about current status.
Case studies
Work we can walk you through
Detailed engagement write-ups are published here as customers approve them. In the meantime we are happy to walk you through reference architectures and how comparable platforms are designed and operated.
Insights
From the engineering team
24 August 2026
Data localization is an architecture problem before it is a legal one
Most residency programmes stall because nobody has mapped where data actually goes. Start with classification and data flow, not with procurement.
15 August 2026
What running AI on local infrastructure actually requires
GPUs are the least of it. The work is in retrieval pipelines, access control, capacity planning and evaluation — and in deciding what genuinely has to stay local.
6 August 2026
Managed Kubernetes: the questions to ask before you sign
Everyone says they manage Kubernetes. The differences show up in upgrades, on-call, and who is holding the pager at 3 a.m.
FAQ
Questions we are asked first
For us it means three concrete things: the infrastructure is operated locally by a named organization, you can identify the facility your workloads run in, and the people who operate the platform are reachable and accountable under local arrangements.
It does not mean a badge. If a specific regulation applies to you, your legal and compliance teams define what it requires; we design and operate infrastructure to support that definition and give you the technical evidence.
No platform makes an organization compliant on its own. Compliance depends on how you classify data, what your applications do with it, your contracts, and your internal controls.
What we provide is infrastructure that can be designed around your requirements — placement of data, access control, audit logging, encryption, backup location and retention — together with documentation of how it is configured.
No. Hosting stops at the server. We provide cloud infrastructure, AI infrastructure and a managed application platform: Kubernetes, managed databases, object storage, GPU compute, delivery pipelines, monitoring, backup, and the engineering team that operates all of it.
Usually, yes. Many applications move as they are, onto virtual machines or containers, and are modernised later where it pays off. We would rather migrate something that works and improve it deliberately than start with a rewrite that takes a year.
Backups are designed per workload rather than applied uniformly, and recovery is tested rather than assumed:
- Agreed RPO and RTO for each application tier
- Encrypted backups with defined retention and isolation from the source environment
- Scheduled restore drills with recorded results
- A runbook written for whoever is on call, not for the person who built it
Let’s discuss your infrastructure.
Tell us what you run today, where the data has to stay, and what you would rather not operate yourselves. We will come back with an architecture and a straight answer.