Production AI systems live or die on the infrastructure underneath them. These are the technologies, APIs, and platforms our engineers deploy every week — chosen for performance, reliability, and the freedom to swap any layer without rewriting the system.
Four technologies show up in nearly every AI system we ship. Not because of contracts — because of the gap between the work they do and the next best alternative.
Foundation Models
GPT-4o, GPT-5, and the o-series for reasoning. The default provider when latency, multimodal capability, and tool-use reliability matter together. Heavily evaluated against every new release.
Foundation Models
Claude 4.5 Sonnet and Opus for long-context, document-heavy workloads, and high-stakes reasoning. The model we reach for when accuracy on adversarial inputs is non-negotiable.
Cloud Infrastructure
Compute, storage, queueing, and Bedrock for managed model hosting. The default substrate for enterprise deployments where compliance, regional control, and vendor maturity move first.
Edge & Frontend
Edge functions, AI SDK, and the global CDN. The deployment layer for customer-facing surfaces — dashboards, AI copilots, and conversational UIs that need sub-200ms response anywhere in the world.
Every active integration in our deployment toolkit, organized by layer. Click a category to focus the grid.
OpenAIAnthropic
Gemini
Llama
Hugging Face
Cohere
Replicate
LangChain
PyTorch
TensorFlowAWS
Google Cloud
Azure
CloudflareVercel
Fly.io
Railway
Render
Postgres
Supabase
MongoDB
Redis
Pinecone
ClickHouse
Snowflake
S3
Swift
Kotlin
Xcode
Android Studio
Flutter
Firebase
Fastlane
Gradle
TypeScript
Python
Node.js
Next.js
React
Tailwind
Docker
Kubernetes
Terraform
GitHub
Stripe
Twilio
Plaid
Slack
WhatsApp
Resend
Auth0
Datadog
Sentry
Grafana
OpenTelemetry
PostHog
PlausibleLogos shown represent technologies we actively deploy. They do not imply official partnerships or endorsements. Selection is project-driven and reviewed against best-in-class alternatives every quarter.
A composable seven-layer stack. Each layer has a default choice and at least one tested alternative — so the system stays portable, even as the market underneath it shifts every quarter.
We never let the system get locked into a layer it can't replace. If OpenAI raises prices 4×, the orchestration layer swaps to Anthropic in a day. If a client mandates EU sovereignty, the data layer moves from a US hyperscaler to a Frankfurt-hosted alternative without rewriting the application.
This is the difference between a system you own and a system that owns you.
AI consultancies that recommend one vendor are selling the vendor. Our ecosystem is the product — and these four principles are why it stays defensible.
We benchmark frontier models against your actual workload every quarter. The system swaps the underlying model when a better one ships — without you renegotiating a contract.
AWS, GCP, Azure, or self-hosted on your own infrastructure. We ship the same architecture across all four — so where the data lives is your decision, not your vendor's.
Each tool earns its place on the stack against measurable criteria. No partner kick-backs, no "preferred vendor" agreements that quietly steer the recommendation.
Code, IP, models, and pipelines belong to you on day one. If we stop being the right partner, you keep running the system the next day — no handoff, no ransom.
The technologies, platforms, and APIs listed throughout this page represent the active stack our engineers deploy at production scale. Logos and brand marks are the property of their respective owners and appear here solely to identify the tools we work with. Inclusion does not imply official partnership, sponsorship, or endorsement. Stack selection is project-driven and re-evaluated each quarter against the best alternatives available.
Twenty-minute call. We map your workload to the right layer of the ecosystem and tell you what we'd build — including what to leave out, and which existing vendor to keep.