Workflow

How we forge AI systems

A four-stage system we use to turn manual chaos into self-running operations. Each stage is a deliverable — not a phase to skip.

STEP 01

Analyze

Typical duration: 1–2 weeks

We audit your stack, workflows, and data to find the highest-leverage automation opportunities.

Discovery interviews

We talk to operators, engineers, and leadership to map how work actually happens.

Data & systems audit

Inventory of every tool, API, database, and integration. We document the truth, not the org chart.

Bottleneck analysis

Time-and-motion analysis to find the costliest manual processes.

ROI report

A written report ranking automation candidates by impact and effort. You decide what to build.

Tools we use:NotionMiroLinearOpenAI APIs for analysis
STEP 02

Build

Typical duration: 4–12 weeks

Custom apps, models, and integrations engineered around your exact stack. No off-the-shelf shortcuts.

Architecture & design

Technical architecture document, data flow diagrams, security review.

Engineering sprints

Weekly sprints with demos. You see progress every Friday, not at the end.

Testing & QA

Unit tests, integration tests, and load testing. We ship code that survives production.

Security & compliance

SOC 2 considerations, data encryption, audit logging where required.

Tools we use:Next.js / ReactPython / FastAPIPostgresAnthropic Claude / OpenAIVercel / AWS
STEP 03

Automate

Typical duration: 2–4 weeks per workflow

AI agents, RPA, and event-driven pipelines take over repetitive work — 24/7, with zero handoff loss.

Pipeline orchestration

Event-driven workflows that handle errors, retries, and edge cases gracefully.

AI agent deployment

Multi-step agents with tools, memory, and human-in-the-loop where it matters.

Integrations

Connect your CRM, billing, support, and internal tools — bidirectional sync.

Monitoring

Dashboards for every automation: success rate, latency, cost per run.

Tools we use:n8n / TemporalLangGraphZapier (when it fits)Custom Python orchestrators
STEP 04

Scale

Typical duration: Ongoing

Monitoring, retraining, and continuous deployment so your systems compound in value over time.

Performance monitoring

Real-time alerts, latency tracking, and cost optimization.

Model retraining

As your data grows, we tune prompts and fine-tune models to keep accuracy high.

Continuous deployment

New features and improvements ship weekly without service interruption.

Team enablement

Documentation, training, and handoff so your team owns what we built.

Tools we use:Datadog / GrafanaGitHub ActionsSentryCustom dashboards

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