ZovraLabs
Technology

State-of-the-art engineering, on the cloud you choose

We're fluent across AWS, Azure and Google Cloud, and model-agnostic across Claude, Gemini, GPT and open-weight models. We pick the right tools for your system, and build it to last.

Start a projectBrowse the stack
  • aws
  • MA

3

Major clouds we design, build and run systems on

50+

Technologies we build with in production

5+

Model families we evaluate for every AI use case

Cloud platforms

AWS, Azure and Google Cloud. Done properly.

We deploy into your own cloud accounts, on the platform your organisation already trusts, using infrastructure as code from the first commit.

awsAI via Amazon Bedrock

AWS

Event-driven platforms, serverless back ends and Bedrock-powered AI inside your AWS organisation.

Key services we use

  • Amazon EKSKubernetes for multi-tenant products and portals
  • AWS LambdaServerless APIs, integrations and event handlers
  • Amazon BedrockClaude, Mistral and Llama with private networking
  • Aurora PostgreSQLRelational data with global failover
  • EventBridge & Step FunctionsEvent routing and orchestrated workflows
  • Control Tower & KMSLanding zones, guardrails and managed keys

What we typically build here

Shipper & customer portalsSaaS productsQuoting engines
MAAI via Azure OpenAI

Azure

Enterprise systems that live alongside Microsoft 365, Entra ID and Dynamics, with Azure OpenAI built in.

Key services we use

  • Azure Kubernetes ServiceContainer platforms for core business systems
  • Azure FunctionsServerless integrations and background jobs
  • Azure OpenAIGPT models with enterprise data controls
  • Entra IDSSO, conditional access and B2B identity
  • Azure SQL & Cosmos DBTransactional and globally distributed data
  • Service Bus & Key VaultReliable messaging and secrets management

What we typically build here

AI-native CRMsCopilots in TeamsClaims & case systems
AI via Vertex AI

Google Cloud

Data-heavy platforms and analytics on BigQuery, with Gemini and custom models on Vertex AI.

Key services we use

  • Google Kubernetes EngineAutopilot clusters for resilient services
  • Cloud RunServerless containers that scale to zero
  • BigQueryServerless warehouse for analytics and ML
  • Vertex AIGemini, Claude and custom model hosting
  • Pub/Sub & DataflowStreaming ingestion and transformation
  • AlloyDB & Cloud KMSPostgreSQL at scale with customer-managed keys

What we typically build here

Data platformsHealthcare systemsForecasting & ML
AI stack

Model-agnostic AI, engineered for production

We don't resell a model. We route each task to the model that does it best (Claude, Gemini, GPT, Mistral or open-weight) and wrap it in retrieval, evals and guardrails, so you can swap providers without rebuilding your system.

  • No training on your data, ever
  • Private endpoints inside your cloud account
  • Every answer traced, evaluated and costed

  1. Experience

    Where people meet the AI

    MT
    Web & mobile appsCopilots in Teams & SlackPortalsAPIs

  2. Agents & workflows

    Reasoning, tools and approvals

    Tool-calling agentsDurable workflowsHuman-in-the-loopMulti-agent orchestration

  3. Models

    Routed per task, swappable

    AO
    ClaudeGeminiGPTMistralOpen-weight

  4. Data & retrieval

    Grounding in your knowledge

    Vector & hybrid searchDocument pipelinesKnowledge graphsWarehouse & lakehouse

  5. Cloud infrastructure

    In your accounts, your regions

    awsMA
    Kubernetes & serverlessPrivate networkingManaged keysGPU inference
Evals · Guardrails · Tracing · Cost controls
Reference architecture · adapted to every system we build

Retrieval (RAG)

Chunking, embeddings, hybrid search and re-ranking tuned to your documents, with citations on every answer.

Evals

Golden datasets and automated eval suites run on every change, so quality is measured rather than assumed.

Guardrails

Input and output filtering, PII redaction, policy checks and approval steps for high-impact actions.

LLMOps

Prompt and model versioning, tracing, cost budgets and drift alerts across every model in production.

Tech directory

The stack behind the systems we build

Search the languages, platforms, data tools and business systems our engineers work with every day. If it's not here, we can still integrate with it.

52 technologies

  • awsCore stack

    Amazon Web Services

    Cloud

    Landing zones, serverless, EKS and Bedrock-powered AI.

  • MACore stack

    Microsoft Azure

    Cloud

    Enterprise workloads, AKS, Entra ID and Azure OpenAI.

  • Core stack

    Google Cloud

    Cloud

    GKE, BigQuery and Vertex AI for data-heavy systems.

  • Cloudflare

    Cloud

    Edge delivery, zero-trust access and WAF.

  • Core stack

    Anthropic Claude

    AI & Models

    Reasoning-heavy agents and long-context analysis.

  • AB

    Amazon Bedrock

    AI & Models

    Managed foundation models inside your AWS account.

  • AO

    Azure OpenAI

    AI & Models

    GPT models with Azure enterprise controls.

  • VA

    Vertex AI

    AI & Models

    Gemini and custom models on Google Cloud.

  • Google Gemini

    AI & Models

    Multimodal models for documents, images and video.

  • Mistral AI

    AI & Models

    Efficient open-weight models for private deployment.

  • Hugging Face

    AI & Models

    Open models, fine-tuning and evaluation.

  • LangChain

    AI & Models

    Agent orchestration and tool calling.

  • PyTorch

    AI & Models

    Custom model training and fine-tuning.

  • Qdrant

    AI & Models

    High-performance vector search for RAG.

  • TypeScript

    Engineering

    Type-safe front ends and services.

  • Core stack

    Next.js

    Engineering

    Fast, SEO-friendly web apps and portals.

  • React

    Engineering

    Rich, accessible product interfaces.

  • Node.js

    Engineering

    APIs and real-time services.

  • Core stack

    Python

    Engineering

    AI services, data pipelines and automation.

  • FastAPI

    Engineering

    High-performance Python APIs.

  • Go

    Engineering

    Low-latency, high-throughput services.

  • GraphQL

    Engineering

    Flexible APIs for complex data models.

  • Flutter

    Engineering

    Cross-platform mobile apps from one codebase.

  • Temporal

    Engineering

    Durable workflows that survive anything.

  • Core stack

    PostgreSQL

    Data & Streaming

    Our default relational database.

  • Core stack

    Snowflake

    Data & Streaming

    Cloud data warehouse and data sharing.

  • Databricks

    Data & Streaming

    Lakehouse for analytics and ML.

  • Google BigQuery

    Data & Streaming

    Serverless analytics at petabyte scale.

  • Apache Kafka

    Data & Streaming

    Event streaming between systems.

  • Apache Airflow

    Data & Streaming

    Orchestrated data pipelines.

  • MongoDB

    Data & Streaming

    Flexible document storage.

  • Redis

    Data & Streaming

    Caching, queues and real-time features.

  • Elasticsearch

    Data & Streaming

    Full-text and hybrid search.

  • Sa

    Salesforce

    Business Systems

    Integrate, extend or migrate off.

  • HubSpot

    Business Systems

    Marketing and CRM data, connected.

  • Core stack

    SAP S/4HANA

    Business Systems

    Quote-to-cash, orders and inventory in real time.

  • MD

    Microsoft Dynamics

    Business Systems

    Integrate, extend or migrate off.

  • Stripe

    Business Systems

    Payments, billing and subscriptions.

  • Shopify

    Business Systems

    Commerce back ends and B2B storefronts.

  • Zendesk

    Business Systems

    Service data on every customer record.

  • Jira

    Business Systems

    Delivery workflows linked to customers.

  • MT

    Microsoft Teams

    Business Systems

    Copilots and approvals where people work.

  • Tw

    Twilio

    Business Systems

    SMS, voice and WhatsApp messaging.

  • PB

    Power BI

    Business Systems

    Governed dashboards for leadership.

  • Core stack

    Kubernetes

    DevOps & Security

    Portable, resilient container platforms.

  • Terraform

    DevOps & Security

    Infrastructure as code across every cloud.

  • Docker

    DevOps & Security

    Reproducible builds and environments.

  • GitHub Actions

    DevOps & Security

    CI/CD with security scanning built in.

  • Datadog

    DevOps & Security

    Observability across apps and infra.

  • Grafana

    DevOps & Security

    Open-source dashboards and alerting.

  • Okta

    DevOps & Security

    SSO, SCIM and lifecycle management.

  • Auth0

    DevOps & Security

    Customer identity for portals and apps.

How we choose technology

Principles over preferences

Every recommendation we make is written down, with the trade-offs, so your team understands why the stack looks the way it does.

  1. 01

    Your problem first

    We choose technology after we understand the workflow, the data and the constraints, never before.

  2. 02

    Boring where it counts

    Proven databases, languages and clouds for the core. We save novelty for where it creates an edge.

  3. 03

    Model-agnostic by design

    A model gateway and eval suite mean you can switch providers when a better or cheaper model ships.

  4. 04

    Your cloud, your standards

    We build on the platform your organisation already runs, following your security and procurement rules.

  5. 05

    No lock-in

    Open standards, infrastructure as code and documented architecture decisions. Your team can take over any time.

  6. 06

    Total cost, not list price

    We model run-cost, licences and the people needed to operate a stack before we recommend it.

Not sure which stack fits?

Tell us about your system and your constraints. We'll recommend an architecture, explain the trade-offs and show you the total cost of running it.

Talk to an architect