01
Demos don't survive contact with production.
Latency, hallucination, cost, and edge cases turn a great demo into an incident. We engineer for the day after launch.
AI-native engineering studio
Senior engineers, pro·ductive from day one.
We embed senior AI engineers into your team and ship production LLM apps, agents, and secure ML systems. Not slideware. Working software, in your repo, on your roadmap.
2–5 days to embedSenior engineers onlyMumbai · San Francisco
Query
Retrieval12ms
LLM core
Tools
Guardrails
Output90ms p95
247 req/s
Trusted by engineering teams at
Why this is hard
Most AI projects die in the gap between a demo and production.
The prototype impresses everyone. Then reliability, security, evals, and scale arrive — and the team that built the demo isn’t the team that can ship it. That gap is where we live.
02
Hiring senior AI talent takes months you don't have.
The market for engineers who've actually shipped LLM systems is brutal. We embed them this week.
03
Security is bolted on, not built in.
Prompt injection, data leakage, and model abuse are real attack surfaces. We treat them as first-class from line one.
What you get
AI engineering and product development services.
One senior team that takes an AI product from architecture to scaled, production-grade reality — without the handoffs.
AI Engineering
Build AI-powered products that ship to production. From LLM integrations to AI agents and RAG systems — solutions built on proven engineering practices that scale with your business.
LLM ApplicationsAI AgentsRAG SystemsFine-tuningMLOps
Product Engineering
Ship faster with a full-stack team that builds AI-integrated products. Clean, maintainable code and modern workflows that accelerate your time to market.
React & Next.jsNode.js & PythonAPI Development
Experience Design
Design intuitive AI-powered products users love — from conversational interfaces to intelligent dashboards that drive engagement.
AI UX DesignUser ResearchDesign Systems
Cloud & DevOps
Scale your infrastructure for AI workloads — cloud architecture for ML and LLM deployments, with CI/CD pipelines built for AI-specific needs.
AWS & GCPKubernetesGPU Optimization
Web & Mobile Development
Build AI-enhanced apps across every platform — fast, intelligent experiences with seamless AI integrations on web, iOS, and Android.
React NativeiOS & AndroidAI-Powered Apps
The operating model
Think · Build · Measure
An infinite loop of critical thinking, diligent execution, and honest measurement. Every solution analyzed, shipped, and proven — then sharpened again.
01 / Think
Strategy & architecture
We start with your real constraints — not a generic playbook. Discovery, technical assessment, and a roadmap with clear ROI milestones. You get an architecture, not a 60-slide deck.
02 / Build
Ship & iterate
Senior engineers embed and ship from week one. Your tools, your repo, your sprint rhythm. Weekly demos, production code, no theatre.
03 / Measure
Outcomes & ROI
We track what moves your business — latency, accuracy, cost, adoption, revenue. Transparent reporting and an honest read on what to do next.
Engagement model
Your team, extended — not replaced.
We slot into how you already work. No statements of work that read like legal documents, no offshore black box.
Week 1
Embed
Senior engineers join your standups, repo, and Slack. We map the system and agree on what “shipped” means.
Week 2–4
Ship
First production increment lands. Weekly demos, real telemetry, tight feedback loops.
Ongoing
Scale
We harden, secure, and scale — and transfer knowledge so your team owns it long after we leave.
The numbers
Proof, not promises.
5d
To first deployment
3+
Years average partnership
40+
Production AI systems shipped
4.9/5
Glassdoor rating
Proven results
AI that ships. Results that matter.
SaaS & TechnologyScaling Observability Platform with 42M Data Points per Minute During Live Sports
Embedding into a live-event observability platform to sustain 42M telemetry data points per minute across cricket and World Cup broadcasts, with a 99.9% SLA and 2-3 hour MTTR during match windows.
42M
Data Points/Min
99.9%
SLA
3
Tournament Types
Observability EngineeringFrontend Engineering
EdTechThe Architecture Shift That Took School Scheduling to 30+ Districts Seamlessly
How Procedure re-architected Timely’s school scheduling platform to scale seamlessly across 30+ districts with faster onboarding and zero data fragmentation.
30+
School Districts
50%
Less Code
0
Migration Downtime
Backend Development
TelecommunicationsDesigning Mission-Critical Communication Software from Scratch
A case study on MCLabs’ rapid development of mission-critical communication software, from concept to production in record time.
100%
Mission-Critical Uptime
2X
Faster Field Coordination
24/7
Emergency-Ready
Product Design
What started with one engineer nearly three years ago has grown into a team of five, each fully owning their deliverables. They’ve taken on critical core roles across teams. We’re extremely pleased with the commitment and engagement they bring.
Shrivatsa Swadi
Director of Engineering · Setu
Life at Procedure
Senior people. Real ownership. No theatre.
We’re a team of engineers who care about craft — mentoring sharp people, shipping work we’re proud of, and being trusted like owners from day one. A Certified Best Workplace, rated 4.9 on Glassdoor.
4.9
Glassdoor rating
Best
Certified workplace
Remote
First, by default
Owners
Not resources
Let’s build
Tell us what you’re shipping.
We’ll tell you who to embed and how fast we can start. First call is with an engineer, not a salesperson.
2–5 days to startSenior engineers onlyhello@procedure.tech
Common questions
What engineering leaders ask before booking a call
We build production AI products: LLM apps, AI agents, retrieval-augmented generation (RAG) systems, and model-powered workflows for web and mobile products.
We work with startup, scale-up, and enterprise product teams that need senior AI engineering capacity to ship quickly without compromising quality, security, or reliability.
Most engagements start in 2-5 business days. We align engineers to your stack and roadmap, then embed into your team rituals and delivery process immediately.
You can start with an AI Sprint for validation, then scale with embedded engineers for feature delivery and platform hardening. We tailor team shape to roadmap scope.
AI Sprints typically range from $15K-$50K. Ongoing embedded engineering starts around $50K/month depending on team size, complexity, and compliance requirements.
Validation and prototypes usually take 2-4 weeks. MVP delivery often lands in 8-12 weeks. Larger enterprise rollouts can span 3-5 months based on integrations and governance.
We build secure-by-default systems with access controls, data handling guardrails, and audit-ready engineering practices aligned to enterprise compliance expectations.
Our engineers ship production code with your team, not slide decks. We focus on measurable delivery outcomes, knowledge transfer, and systems your team can operate long-term.