Technologies
Our engineering stack — end to end
DiveScale picks the right tool for the job — not the trendiest one. Below are the 39 platforms, languages, and frameworks we deploy in production for clients across the US, UK, and Europe.
AI Platforms
Foundation models and AI providers we deploy in production.
OpenAI
Production-grade integrations with GPT-4o, GPT-4.1, o-series reasoning models, Realtime voice, embeddings, and the Assistants API.
Learn moreAnthropic (Claude)
Production builds on Claude Opus, Sonnet, and Haiku — long-context reasoning, tool use, prompt caching, and Computer Use agents.
Learn moreGoogle Gemini
Production Gemini integrations on Vertex AI and the Gemini API — multimodal, long-context, and grounded with Google Search.
Learn moreLLaMA
Self-host Meta’s LLaMA family for private, controllable, and cost-predictable AI — on your VPC or our managed infrastructure.
Learn moreDeepseek
Production deployment of Deepseek-V3 and Deepseek-Coder for reasoning, coding, and high-volume workloads at a fraction of frontier-model cost.
Learn moreOllama
Ship private, offline-capable AI features with Ollama — local LLM serving for desktops, edge servers, and air-gapped enterprises.
Learn moreAI Capabilities
End-to-end AI patterns we design, ship, and operate.
Generative AI
End-to-end generative AI engineering — strategy, prototype, evaluation, and production for text, image, audio, and code.
Learn moreLLMs
Production LLM engineering — model selection, RAG, fine-tuning, evals, guardrails, and the operational layer that keeps quality high.
Learn moreAgentic Workflows
Multi-step AI agents that plan, call tools, write to systems, and stay inside policy — with human-in-the-loop checkpoints where it matters.
Learn moreMLOps
MLOps platform engineering — pipelines, model registries, evaluation, monitoring, and incident response for ML and LLM systems.
Learn moreLanguages & Frameworks
Server-side languages and frameworks we ship products with.
Python
Production Python engineering — FastAPI services, async pipelines, AI/ML workloads, data engineering at scale, and the typed, tested, observable discipline production Python deserves.
Learn moreJavaScript
Production JavaScript engineering across modern web frameworks, Node services, and edge runtimes — fluent in the ecosystem and disciplined about its sharp edges.
Learn moreTypeScript
End-to-end typed engineering — React, Next.js, NestJS, Node, and shared schemas — with the discipline TypeScript was built for.
Learn moreNode.js
Production Node.js engineering — NestJS, Fastify, Hono, real-time systems, job queues, and the operational discipline that single-threaded runtimes demand.
Learn moreGo
Production Go engineering — high-performance APIs, infrastructure tools, and concurrent systems where latency and throughput matter.
Learn moreDjango
Production Django and Django REST Framework — admin-heavy products, typed services, and the operational layer enterprise teams expect.
Learn moreFrontend
Modern web UI frameworks for fast, accessible experiences.
React
Production React engineering — Server Components, design systems, performance discipline, accessibility, and the build tooling modern apps deserve.
Learn moreNext.js
Production Next.js engineering — App Router, RSC, edge runtime, ISR, SEO-first metadata, and the deployment topology that fits your workload (Vercel or self-hosted).
Learn moreAWS
AWS-native services for compute, orchestration, and serverless.
AWS
AWS architecture, migration, and platform engineering — multi-account governance, well-architected workloads, Terraform IaC, and the operational discipline production demands.
Learn moreAmazon EC2
EC2 architecture, AMI pipelines, Auto Scaling, Spot/Graviton optimization, and the operational layer production compute requires.
Learn moreAmazon EKS
EKS cluster engineering — IAM Roles for Service Accounts, autoscaling with Karpenter, GitOps with Argo CD, and the observability stack production Kubernetes demands.
Learn moreAmazon ECS
ECS and Fargate platform engineering — task definitions, capacity providers, blue/green deploys, and the operational layer container workloads need.
Learn moreAWS Lambda
Lambda function design, optimization, and operations — cold-start mitigation, IAM scoping, observability, and the architectures where serverless wins.
Learn moreAWS SAM
Serverless apps defined and shipped with AWS SAM — Lambda, API Gateway, Step Functions, and everything you need to deploy from a single template.
Learn moreAWS CloudFormation
CloudFormation and CDK engineering — stack design, drift detection, StackSets across accounts, and the IaC discipline production AWS demands.
Learn moreCloud Platforms
Azure and Google Cloud for multi-cloud and enterprise workloads.
Microsoft Azure
Azure architecture, App Service, AKS, Functions, and Azure OpenAI — enterprise-grade builds for Microsoft-aligned organizations.
Learn moreGoogle Cloud
GCP architecture, GKE, Cloud Run, BigQuery, and Vertex AI — production engineering for organizations leveraging Google’s data and AI strengths.
Learn moreDevOps & Platform
Pipelines, IaC, and container platforms for reliable delivery.
DevOps
End-to-end DevOps engagements — CI/CD, infrastructure as code, observability, incident response, and the platform that lets your developers ship.
Learn moreDocker
Production Docker engineering — small images, multi-stage builds, BuildKit caching, security scanning, and the operational discipline containers deserve.
Learn moreKubernetes
Production Kubernetes engineering — cluster design, GitOps, observability, CIS hardening, multi-tenancy, internal developer platforms, and the day-2 operations the demos skip.
Learn moreTerraform
Terraform engineering — module design, state strategy, multi-account governance, policy-as-code, drift detection, and CI-driven plan / apply for multi-cloud estates.
Learn moreCI/CD
End-to-end CI/CD engineering — fast builds, deterministic deploys, automated quality gates, and rollback paths that actually work.
Learn moreGitHub Actions
GitHub Actions engineering — reusable workflows, OIDC-to-cloud, runner strategy, and the discipline that turns pipelines into a platform.
Learn moreData & Storage
Relational, document, warehouse, and big-data engines.
PostgreSQL
Production PostgreSQL — schema design, query tuning, replication, partitioning, and the operational discipline a serious database deserves.
Learn moreMySQL
Production MySQL — schema design, query tuning, replication, sharding, and managed deployments on RDS, Aurora, or Cloud SQL.
Learn moreMongoDB
MongoDB engineering — schema design, indexing, aggregation pipelines, Atlas operations, and the discipline to use document storage well.
Learn moreSnowflake
Snowflake data engineering — warehouse design, performance, governance, and the Snowpark/Cortex stack for analytics and AI.
Learn moreBig Data
Production big data engineering at real scale — managing trillions of rows with millisecond query times, custom sharding strategies, ETL pipelines, and lakehouse architectures on Spark, dbt, Iceberg, Snowflake, and BigQuery.
Learn moreIoT
Connected device platforms, edge compute, and telemetry pipelines.
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