01
Demos don't survive contact with production.
Latency, hallucination, cost, and edge cases turn a great demo into an incident. The pod engineers for the day after launch and owns the result.
The Procedure Pod
An AI engineering pod that ships in week one.
Senior engineers plus a delivery lead, in your repo within 5 days. We own outcomes, not hours.
Week-One Guarantee: replace any underperformer free within 14 days. Cancel in the first 30 days, pay nothing.
98% client retention100+ products shipped2-5 days to start
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 team that builds the demo is rarely the team that can ship it.
02
Hiring senior AI talent takes months you don't have.
Engineers who have shipped real LLM systems are scarce. A full pod, senior engineers plus a delivery lead, lands in your repo this week.
03
Security is bolted on, not built in.
Prompt injection, data leakage, and model abuse are real attack surfaces. The pod treats them as first-class from line one.
What you get
AI engineering and product development services.
One pod takes your AI product from architecture to production, with no handoffs.
AI Engineering
Production AI products, not prototypes. LLM integrations, AI agents, and RAG systems built on engineering practices that scale with your business.
LLM ApplicationsAI AgentsRAG SystemsFine-tuningMLOps
Product Engineering
A full-stack pod that ships AI-integrated products. Clean, maintainable code and modern workflows that cut your time to market.
React & Next.jsNode.js & PythonAPI Development
Experience Design
Design AI-powered products users trust, from conversational interfaces to intelligent dashboards that drive real engagement.
AI UX DesignUser ResearchDesign Systems
Cloud & DevOps
Scale 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
Ship AI-enhanced apps across every platform. Fast, intelligent experiences with native AI integrations on web, iOS, and Android.
React NativeiOS & AndroidAI-Powered Apps
The operating model
Think · Build · Measure
The pod owns the loop: analyze, ship, measure, then sharpen again.
01 / Think
Strategy & architecture
The pod starts 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 and a delivery lead embed and ship from week one. Your tools, your repo, your sprint rhythm. Weekly demos, production code, no theatre.
03 / Measure
Outcomes & ROI
The pod owns outcomes, not hours. We track latency, accuracy, cost, adoption, and revenue, with transparent reporting and an honest read on what to do next.
Engagement model
How an AI engineering pod ships inside your team.
A named pod slots into how you already work, no offshore black box.
Week 1
Embed
Senior engineers and a delivery lead join your standups, repo, and Slack. The pod maps the system and agrees on what “shipped” means.
Week 2–4
Ship
The first production increment lands. Weekly demos, real telemetry, and tight feedback loops. The pod owns the outcome.
Ongoing
Scale
We harden, secure, and scale, then transfer knowledge so your team owns it long after the pod rolls off.
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 engineering 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.
The engineers who staff our pods care about craft. We mentor sharp people, ship work we’re proud of, and get 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.
Every week without a senior pod is another sprint of tech debt. Describe what you’re building and we’ll shape the pod that ships it in week one. First call is with an engineer, not a salesperson.
2–5 days to startReplace anyone free in 14 daysCancel in 30 days, pay nothing
Common questions
What engineering leaders ask before booking a call
The Procedure pod builds production AI products: LLM applications, AI agents, retrieval-augmented generation (RAG) systems, and model-powered workflows across web and mobile. A pod pairs senior engineers with a delivery lead, so you get architecture, shipped code, and ownership of outcomes, not a prototype that stalls before production.
Procedure works with startup, scale-up, and enterprise product teams that need senior AI engineering capacity fast. A Procedure pod suits leaders who want to ship quickly without compromising quality, security, or reliability, and who prefer a team that owns outcomes over a body shop that bills hours.
A Procedure pod starts in 2-5 business days. Senior engineers and a delivery lead align to your stack and roadmap, then embed in your standups, repo, and Slack. The pod ships its first production increment in week one, so you see real code before most vendors finish onboarding.
Procedure delivers through a pod: senior engineers plus a delivery lead who owns outcomes. You can start with an AI Sprint to validate, then scale the pod for feature delivery and platform hardening. We shape team size to your roadmap, and you can cancel in the first 30 days at no cost.
With Procedure, AI Sprints typically range from $15K-$50K, and an ongoing pod starts around $50K per month depending on team size, complexity, and compliance needs. A pod bundles senior engineers and a delivery lead into one outcome-focused engagement, so you pay for shipped results, not staffed hours.
A Procedure pod ships a first production increment in week one. Validation and prototypes usually take 2-4 weeks, and MVP delivery often lands in 8-12 weeks. Larger enterprise rollouts can span 3-5 months depending on integrations and governance, with the pod owning outcomes throughout.
The Procedure pod builds secure-by-default systems with access controls, data-handling guardrails, and audit-ready engineering practices aligned to enterprise compliance. Security is treated as first-class from line one, not bolted on later, because prompt injection, data leakage, and model abuse are real attack surfaces in production AI.
A Procedure pod ships production code with your team, not slide decks. Senior engineers and a delivery lead own measurable outcomes, transfer knowledge, and build systems your team can operate long-term. If week one underperforms, we replace anyone free within 14 days, and you can cancel in the first 30 days.