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Our process

AI at every stage, from idea to go-live.

We're not a team that bolts AI on at the end. We use AI across the whole product engineering lifecycle — to move faster at every stage while a senior team keeps the rigor. Here's how we work, and the tools and platforms we use.

01

Discovery & Definition

Every build starts by getting the problem right. We use AI to accelerate research, synthesize requirements, and turn a fuzzy idea into a sharp, validated plan — so we commit to building the right thing, fast.

Research
ClaudeChatGPTPerplexity
Synthesis
NotebookLMClaude Projects
Requirements
AI-assisted PRDsUser-research analysis
02

Product & UX Design

We move from idea to clickable prototype in days. AI generates first-draft flows, wireframes, and UI that our designers refine — and produces the imagery and assets a polished product needs.

Design
Figma AIGalileo AIUizard
UI generation
Vercel v0Claude
Assets & imagery
MidjourneyDALL·EAdobe Firefly
03

Architecture & Planning

Before scaling up, we reason through the system design, data model, and the trade-offs that matter. AI helps us explore options and turn decisions into clear, diagram-backed specs.

Architecture
ClaudeGPT-4-class models
Diagrams-as-code
Eraser AIMermaid
Planning
AI-assisted specs & estimation
04

Engineering & Build

Senior engineers build with AI pair-programmers at their side — shipping production code faster while keeping full ownership of architecture, quality, and review. Speed without the vibe-coded mess.

AI pair programming
Claude CodeCursorGitHub CopilotWindsurf
In-product intelligence
Anthropic Claude API
Environments
Replit
05

Applied AI, ML & Data

This is the intelligent core — where the product actually gets smart. We build models, RAG pipelines, and agents on the leading platforms, with the data and MLOps foundation to run them reliably in production.

Model platforms
Anthropic ClaudeOpenAIGoogle Vertex AIAWS BedrockAzure AI
Models & orchestration
Hugging FaceLangChainLlamaIndex
Vector & retrieval
PineconeWeaviatepgvector
MLOps & evals
SageMakerMLflowWeights & BiasesLangSmith
06

Quality, Testing & Security

We ship with confidence. AI generates and runs tests across the surface area, reviews every change, and helps us find security and edge-case issues a deadline might otherwise hide — plus continuous evals for anything AI-powered.

Test automation
PlaywrightAI test generationmabl
Code review
CodeRabbitAI review
Security
SnykAI-assisted scanning
AI evals
LangSmithContinuous evaluation
07

Deployment, Go-Live & Operate

Going live is the start, not the end. We automate delivery and infrastructure, and use AI-driven observability to catch anomalies, speed up incident response, and feed real usage back into the next iteration.

CI/CD & infra
GitHub ActionsCopilotAI-assisted Terraform
Observability & AIOps
DatadogAnomaly detectionIncident response
Improve
AI usage analyticsContinuous iteration
What stays human

AI accelerates. Senior engineers decide.

Tools change every month — our principles don't. AI does the heavy lifting; people own the judgement.

Senior judgement

Every AI output is reviewed and owned by an engineer who has shipped real products. No unreviewed, vibe-coded shortcuts.

Right tool, right stage

We're tool-agnostic and pick the best model or platform for each job — and swap them as the landscape moves.

Your stack, your IP

We work in your repos and cloud accounts, and everything we build — code, models, assets — is yours.

Want this process on your product?

Tell us what you're building. We'll show you exactly how we'd take it from idea to go-live.

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