Artikate Studio

Tech Stack

Built with the best stack.

We choose tools based on what the project demands — not what is fashionable. Real brand-grade tooling, battle-tested in production at scale, from sovereign AI to high-traffic commerce.

PyTorchNext.jsAWSAWSKubernetesPostgreSQLRazorpay
On-premise GPU cluster and air-gapped infrastructure

The Stack

Every layer, named and proven.

The exact technologies we ship with — grouped by where they live in the stack. Hover any chip to confirm; every one is in production today.

AI & Machine Learning

PyTorchTensorFlowYOLOv8xLlama 3 70BWhisper ASRLangChainRAG PipelinesGGUF QuantisationOpenCVHugging FaceMLflowRLRLHF

Cloud & Infrastructure

AWSAWSGoogle CloudDockerKubernetesTerraformAnsibleCI/CD PipelinesGPU ClustersAir-gapped DeployRedisPostgreSQLpgvector

Frontend & Mobile

Next.js 15React 19React NativeTypeScriptTailwind CSSFramer MotionPWAShopify PlusShopify LiquidHydrogen

Backend & APIs

FastAPIDjangoNode.jsGraphQLREST APIsWebSocketsMicroservicesEvent-driven ArchitectureBullMQCelery

AI Platforms & Models

GPT-4ClaudeLLaMAMIMistralGeminiDEDeepseekQWQwenOpenAI APIAnthropic APIVertex AI

Security & Compliance

Air-gapped SystemsLAN-only DeploymentZero-egress ArchitecturemTLSRBACAudit LoggingGDPRHIPAA-alignedSOC 2 Practices

Delivery Process

How we ship on time, every time.

Consistent delivery is not luck — it is process. Here is how we manage every engagement from first call to long-term partnership.

01
01Day 1–3

First Brief

Deep-dive brief covering security requirements, stack constraints, integration environment, and what "done" means. Architecture Decision Record (ADR) initiated.

Deliverables

  • Constraint mapping
  • Risk register
  • Scope document
  • Signed NDA
02
02Week 1–2

Technical Alignment

Lead engineers map existing systems, APIs, and infrastructure. ADR covers every integration point, data flow, and security boundary before production code begins.

Deliverables

  • Architecture Decision Record
  • Tech stack confirmation
  • Sprint zero
  • Team onboarding
03
032-week cycles

Sprint Delivery

Strict 2-week sprints with live demos at the end of every cycle. Working software every fortnight — not presentations. Blockers escalated within 24 hours.

Deliverables

  • Fortnightly live demos
  • Sprint retrospectives
  • CI/CD pipeline
  • Test coverage reports
04
04Post-launch

Ongoing Partnership

Most clients stay 12–24 months. We embed as an extension of your team with SLA-backed uptime, monthly health reports, and engineers who know your codebase.

Deliverables

  • SLA-backed uptime
  • Monthly health reports
  • Continuous improvement
  • Dedicated engineer

Certifications

Certified where it matters.

AWS Select Partner

Amazon Web Services

Active AWS Partner Network member with delivery across EC2, ECS, Lambda, SageMaker, and Bedrock. Certified for cloud-native and AI workloads.

GCP Partner

Google Cloud

Certified Google Cloud partner with deployments across Vertex AI, BigQuery, GKE, and Cloud Run. Enterprise-scale ML delivery.

Razorpay Technology Partner

Razorpay

Certified Razorpay integration partner for payment gateway, route payments, subscriptions, and UPI flows in D2C and enterprise contexts.

Red Hat Technology Partner

Red Hat

Red Hat partner for enterprise Linux, OpenShift container platforms, and Ansible automation — used in air-gapped on-premise deployments.

FAQ

Technical questions.

We are cloud-agnostic and certified on both AWS and GCP. For most enterprise engagements we recommend GCP (Vertex AI, BigQuery) for AI workloads and AWS for general-purpose cloud infrastructure. For classified or government work, all processing is on-premise — no cloud.

Yes — always. We review your existing technology landscape in the first brief and build around it where possible. We do not rip and replace unless the architecture genuinely demands it.

Yes. A significant portion of our work involves air-gapped, LAN-only, or zero-egress deployments for defence and government clients. We have experience deploying full-stack AI systems on isolated networks with no internet connectivity.

We provision on-premise GPU clusters (NVIDIA A100, H100) or use dedicated cloud GPU instances that are then decommissioned. For classified data, all training happens on client-controlled hardware. We handle the full pipeline: data preparation, training, quantisation (GGUF), and deployment.

We practice test-driven development (TDD) for all backend services and maintain a minimum 80% unit test coverage. For AI systems, we maintain evaluation datasets and run regression tests against model performance benchmarks. All deployments go through staging environments with automated integration tests.

Get Started

Ready to build with
the right stack?

Tell us about your challenge and we will respond with a concrete plan — not a sales deck.