Our Technology

The Stack That Powers Intelligent Cloud

Every tool chosen for production reliability, cloud-native performance, and AI-readiness — from infrastructure orchestration to model serving and real-time data.

Cloud & AI Engineering Stack
🐳

Kubernetes & Istio

Production-grade container orchestration with Istio service mesh — enabling zero-downtime deployments, canary releases, mTLS, and fine-grained traffic management across multi-cluster cloud environments.

🏗️

Terraform & Pulumi

Infrastructure-as-code managing every cloud resource as version-controlled, reproducible code — eliminating configuration drift, enabling rapid environment provisioning, and enforcing security baselines automatically.

Apache Kafka & Flink

High-throughput event streaming and stateful stream processing — the real-time data backbone connecting cloud services, AI models, and operational systems at millions of events per second.

🔥

PyTorch & TensorRT

PyTorch for model development and research, TensorRT for GPU-optimised production inference — delivering cloud-scale AI serving with hardware-specific kernel optimisation and dynamic batching.

🌊

Databricks & Spark

Unified analytics engine for petabyte-scale data processing, ML training, and real-time feature engineering — bridging the data engineering and AI teams on a shared lakehouse platform.

📡

Prometheus & Grafana

Open-source observability foundation — custom metrics, distributed tracing with Jaeger, and AI-augmented alerting that correlates signals across cloud services, applications, and ML models.

🤗

Hugging Face & vLLM

Foundation model ecosystem combined with vLLM's PagedAttention for high-throughput LLM serving — enabling enterprise generative AI at scale with sub-second time-to-first-token and SOC 2 compliance.

🔐

Vault & OPA

HashiCorp Vault for secrets management and PKI, Open Policy Agent for policy-as-code enforcement — the security control layer ensuring every cloud resource and API call meets your compliance requirements.

Our Engineering Principles
01Cloud-Native — containers, serverless, managed services by default
02Infrastructure as Code — everything version-controlled, reproducible
03Shift-Left Security — policy enforcement at design, not deployment
04Observable by Default — metrics, logs, traces on every service
05AI-Native Design — ML embedded in infrastructure, not bolted on
06Zero-Trust — verify everything, assume nothing

Deep Technical Discussion

Our architects love talking infrastructure, AI systems, and cloud design. No sales pitch — just engineering.

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