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AI engineering pods · since 2017

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.

98%
client retention
100+
products shipped
2-5
days to start

Week-One Guarantee: replace any underperformer free within 14 days. Cancel in the first 30 days, pay nothing.

Trusted by engineering teams at
Aster logoESPN logoKredX logoMCLabs logoPine Labs logoSetu logoTenmeya logoTimely logoTreebo logoTurtlemint logoWorkshop Ventures logoMonaire logo
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.

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.

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.

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.

Core practice

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
Engagement model

How an AI engineering pod ships inside your team.

A named pod slots into how you already work, then owns the loop from first commit to measured outcomes. No offshore black box.

  1. 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.

  2. Week 2–4

    Ship

    The first production increment lands in weeks, not quarters. Weekly demos, real telemetry, and tight feedback loops keep the pod on the outcome, not on activity.

  3. Ongoing

    Measure & scale

    We track the outcomes that matter, latency, cost, adoption, and revenue, then harden and scale. Transparent reporting throughout, and we hand knowledge back so your team owns it.

Why Procedure

Built by people who care how the work gets done

You are not renting seats. You get a founder-vetted pod, a delivery lead who owns the outcome, and a partner that sticks around long after the first release.

From one builder to another

We are builders at the core, and we love the craft. That same care goes into everything we ship for you, from the first commit to the last edge case.

Been there, done that

We know what it takes to build a product, because we have done it. Our engineers have shipped inside high-functioning teams, at startups and at scale.

Every engineer, founder-vetted

Our founders still personally hire every engineer against a high bar. We reject far more than we accept, and the bar only rises with each new hire.

A pod built for your problem

We are not a staff-aug shop handing you seats to fill. We assemble a pod matched to what your project actually needs, so the shape of the team fits the work.

High-agency engineers

When a project hits the ceiling, our engineers take ownership and solve it instead of waiting to be told. They move problems forward, not just tickets.

User-obsessed engineers

Our engineers go past the code to become domain experts in your product. Coding is commoditized; what sets an engineer apart is obsession with your users.

A delivery lead with every pod

You will not be left managing the team yourself. Every pod ships with an experienced delivery lead who owns planning, cadence, and communication.

Partners for the long haul

We stay through the ups and the downs, not just the easy stretch. Our average client partnership runs three years, and many run longer.

Born with AI, not bolted on

We have engineered with AI and ML since 2017, years before ChatGPT made it a buzzword. It is native to how we build, not a capability we rebranded into after the hype.

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.

Explore all case studies →
EdTech

From 30 Minutes to 10: Speeding Up CI for an EdTech Team's React Monorepo

Restructuring a GitHub Actions pipeline for an EdTech scheduling platform: caching, artifact reuse, and cleaner job responsibilities took PR wait time from ~30 to ~10 minutes and cut projected CI cost by 73%.

3xFaster PR Feedback
73%Lower CI Cost
6sCoverage Check
SaaS & Technology

Onboarding a Cricket Fantasy Platform Through 980M-Point Match-Day Peaks

Helping an observability platform onboard a fantasy sports customer: Aerospike APM support, dashboard improvements, and stability fixes while sustaining 980M telemetry data points per minute through a live cricket season.

980MData Points/Min
99.9%SLA
0Escalated Incidents
SaaS & Technology

Shipping an APM Pipeline in 10–15 Days Before a Major eCommerce Sale

Helping an observability platform close APM and alerting gaps, fix log-heavy workloads, and support 300–400M telemetry data points per minute before a major ecommerce sale.

300M–400MTelemetry Points/Min
10–15 DaysCode Freeze Lead Time
50+Services Monitored
SaaS & Technology

Scaling 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.

42MData Points/Min
99.9%SLA
3Tournament Types
EdTech

The 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
0Migration Downtime
Telecommunications

Designing 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
2XFaster Field Coordination
24/7Emergency-Ready
Testimonials

Trusted by Engineering Leaders

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
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.

Procedure team jumping at the beach during a Goa offsiteProcedure team at dinner during an offsite
4.9
Glassdoor rating
Best
Certified workplace
Common questions

What engineering leaders ask before booking a call

What does Procedure build for AI teams?

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.

Who is Procedure best suited for?

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.

How fast can your team start?

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.

How do your engagement models work?

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.

How much does AI development 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.

What is a typical delivery timeline?

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.

How do you handle security and compliance?

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.

Why choose Procedure over traditional consulting?

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.

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.

Book a 30-minute call →
2–5 days to startReplace anyone free in 14 daysCancel in 30 days, pay nothing