What Procedure Technologies does

Procedure Technologies, founded in 2017 and headquartered in Mumbai with offices in San Francisco and Melbourne, is a private AI engineering and product development firm operating a forward-deployed pod model. Its core offering, the AI Engineering Pod, places a named team of senior engineers plus a delivery lead inside a client's repository within five days, shipping production AI increments from week one under a 30-day cancel-at-no-cost guarantee and a 14-day free-replacement clause for underperformers. Underlying technical capabilities span LLM applications, AI agents with multi-step reasoning and tool use, retrieval-augmented generation (RAG), fine-tuning, MLOps/LLMOps, predictive analytics, anomaly and fraud detection, NLP, recommendation systems, and computer vision for medical imaging — built on AWS/GCP, Kubernetes, and GPU-optimized infrastructure with documented production benchmarks including 12ms retrieval latency, sub-100ms trading latency, and 980M telemetry data points per minute sustained. The firm serves a mix of startups, scale-ups, and enterprises across Financial Services, Healthcare, Education, SaaS, Telecommunications, and IoT, with named clients including ESPN, Pine Labs, Setu, KredX, Aster, MCLabs, Timely, and Monaire.

The firm monetizes through professional-services engagements: fixed-price AI Sprints at $15K-$50K for 2-4 week prototyping, monthly forward-deployed pod retainers starting around $50K, full product builds at 6-12 week cycles, and enterprise engagements at $500K+. Go-to-market is engineer-led direct sales (no salespeople on the first call), supported by deep technical content marketing, named case studies, and the Mumbai Meets AI community meetup. The company has been bootstrapped since founding with no external funding disclosed, and reports 40+ engineers, 75+ clients, 150+ projects shipped, 98% client retention, and 3+ year average partnership length — backed by a 4.9 Glassdoor rating and TSOW Certified Best Workplace recognition for 2025-26 and 2026-27.

Name

Procedure Technologies

Legal name

Procedure Technologies

Website

https://procedure.tech

Company type

Private

Founded year

2017

Operating status

Operating

Headcount range

51–100 employees

Short description

Procedure Technologies is a private AI engineering firm founded in 2017 that embeds senior engineering pods inside client teams within five days to ship production AI systems, serving startups, scale-ups, and enterprises across Financial Services, Healthcare, Education, and SaaS.

Ownership category

akta.pro rank

Product category

Custom AI Software Development Services

NAICS

Custom Computer Programming Services (541511), Computer Systems Design and Related Services (5415), Computer Systems Design Services (541512), Other Computer Related Services (541519)

SIC

Services-Computer Programming Services (7371), Services-Computer Programming, Data Processing, Etc. (7370), Services-Computer Integrated Systems Design (7373)

akta.pro primary industry

AI/ML Engineering & Model Development Services (BPAEAHAF)

akta.pro secondary industries

LLMOps & Generative AI Platforms (Prompt/Agent Orchestration, RAG) (HDAEANAD), Observability, Monitoring & AIOps (BPAEAKAG), End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)

Keywords

• AI engineering services
• Forward-deployed engineering
• LLM application development
• AI agent development
• Production AI systems

Headquarters

HQ city

Mumbai

HQ country

India

HQ region

Asia

Offices3 records

Markets served

GTM type

B2B

Offering type

Services

Cost components

Personnel, Technology or R&D, Operations, Marketing or Sales, Infrastructure

Revenue model

1. AI Sprint (Fixed-Price Project): A focused 2-4 week rapid prototyping engagement to validate AI concepts before larger investment. Produces reusable production code and a roadmap for full deployment.
2. Forward-Deployed Engineering Pod (Monthly Retainer): A dedicated pod of senior engineers plus a delivery lead embedded in the client's team, billed on a monthly retainer basis. The pod owns outcomes, not hours. Team size scales to the client's roadmap.
3. Full Product Build (Fixed-Price, Outcome-Based): End-to-end delivery of an entire AI-powered product from first commit to production launch, typically 6-12 weeks, with complete IP ownership transferred to the client.
4. Staff Augmentation / Scale-Up Engagements: Individual or small-team augmentation where engineers integrate directly into the client's existing workflows, billed on a per-engineer monthly basis.

Pricing tiers

Go-to-market motion1 record

Distribution channels2 records

Marketing channels7 records

Core offering

Procedure Technologies sells an "AI Engineering Pod" — a named team of senior engineers plus a delivery lead that embeds inside a client's repository within 2–5 days and ships a first production AI increment in week one. The pod owns measurable outcomes (latency, accuracy, cost, adoption, revenue) rather than billed hours, and ships production-grade LLM applications, AI agents, RAG systems, MLOps/LLMOps, and full-stack product engineering from architecture through deployment. Supporting offerings include AI Sprints (2–4 week fixed-price prototypes), Full Product Builds (6–12 week end-to-end), and industry-specific solution packages for Financial Services, Healthcare, Education, and SaaS.

Product overview

Procedure Technologies operates as an AI engineering and product development firm offering the AI Engineering Pod as its core offering — a dedicated team of senior engineers plus a delivery lead that embeds in client repositories within 5 days, ships production AI increments from week one, and owns measurable outcomes. The portfolio includes AI Engineering Services (system architecture, model development, data pipelines, MLOps), AI Agents Development (autonomous agents with multi-step reasoning), AI Sprints (2-4 week rapid prototyping at $15K-$50K), and Full Product Build (end-to-end delivery in 6-12 weeks). Supporting services span Frontend, Backend, Mobile, and Cloud/DevOps engineering, plus dedicated QA. Delivery models include Forward-Deployed Engineering for embedded teams, Scale-Up Engineering for growth-stage augmentation, Startup AI Development for MVP builds, and Enterprise AI Development for compliance-first deployments. Industry-specific AI solutions target Financial Services (sub-100ms trading AI, fraud detection), Healthcare (HIPAA-compliant clinical AI, medical imaging), Education (adaptive learning, AI tutoring), and SaaS (AI copilots, intelligent search). The company has a certified best workplace culture (4.9 Glassdoor rating, TSOW certified) and operates from San Francisco, Mumbai, and Melbourne.

Differentiator

Problem solved

Functional benefit

Products and services

• AI Engineering Pod A named team of senior engineers plus a delivery lead that embeds in the client's repository within 5 days, ships production AI increments from week one, and owns measurable outcomes. Bundled with a 30-day cancellation guarantee and 14-day free underperformer replacement. Sold as the flagship engagement for AI-enabled product teams.
• AI Sprints A 2–4 week fixed-price rapid-prototyping engagement ($15K–$50K) that compresses months of AI exploration into focused sprints, delivering working prototypes with reusable production code and a roadmap for full deployment.
• Full Product Build End-to-end fixed-price delivery of an entire AI-powered product from first commit to production launch in 6–12 weeks, with complete IP ownership transferred to the client. One accountable team, zero handoffs.
• Forward-Deployed Engineering Embedded senior engineers placed directly inside client organizations; attend standups, use client tools, and ship production code alongside the client's team, with the first PR typically merged within 72 hours.
• Scale-Up Engineering Growth-stage team augmentation that adds senior AI and engineering talent within 5 days, with flexible team composition scaled to roadmap priorities and built-in knowledge transfer.
• Startup AI Development MVP development for early-stage companies delivering functional AI products in 4–8 weeks, including investor-ready architecture, technical due-diligence preparation, and fractional CTO support.
• Enterprise AI Development Compliance-first AI development meeting enterprise security requirements, covering SOC 2, HIPAA, and GDPR with audit-ready architecture and enterprise procurement workflows.
• AI Agents Development Builds autonomous AI agents that reason through complex tasks, use tools and APIs, and execute multi-step workflows, with multi-agent orchestration, human-in-the-loop workflows, memory management, and safety guardrails.
• AI Engineering Services Production-ready AI system services covering AI system architecture, model development and integration, data pipelines, MLOps/LLMOps, AI application development, and AI system monitoring and optimization.
• Product Engineering Full-stack development covering React and Next.js, Node.js and Python, and API development, building AI-integrated products with clean maintainable code and modern workflows.
• Cloud & DevOps Cloud architecture for ML and LLM deployments on AWS and GCP, Kubernetes setup, GPU optimization, and CI/CD pipelines built for AI-specific needs.
• Experience Design AI UX design, user research, and design systems for AI-powered products including conversational interfaces and intelligent dashboards.
• AI for Financial Services Sub-100 ms AI for trading, risk, and fraud detection with SOC 2 compliant deployments, real-time ML infrastructure, and algorithmic trading systems. Includes $47M+ fraud prevented and 99.99% uptime on critical trading systems.
• AI for Healthcare HIPAA-compliant AI for clinical workflows, diagnostics, and medical image analysis, including clinical decision support, patient flow optimization, and FDA regulatory pathway support.
• AI for Education Adaptive learning systems, AI tutoring, content generation, and automated assessment for EdTech, with WCAG 2.1 AA accessibility compliance and measurable learning outcome improvements.
• AI for SaaS & Technology AI copilots, intelligent search, automated workflows, and AI-powered analytics for SaaS products, focused on sustainable AI costs and feature-adoption metrics.

Quantifiable outcome

• 98% client retention rate
• +9 more outcomes

Named customers14 records

Segments5 records

Ideal customer profiles5 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration2 records

AI capability13 records

Feature8 records

Scale indicators28 records

Recent moves7 records

Expansion highlights6 records

Direct peers

• Thoughtworks: Global technology consultancy that embeds cross-functional engineering teams with clients to ship production software and AI systems, with comparable outcome-oriented delivery models and a similar premium on senior engineering talent.
• Globant: Large digital engineering services firm offering AI pod-style teams and enterprise AI solutions across verticals, with comparable project-based and retainer delivery and a similar emphasis on production-grade AI rather than demos.
• Tribe AI: AI-native services firm that staffs vetted AI engineers into client teams to ship production AI applications, operating a near-identical forward-deployed pod model targeting startup, scale-up, and enterprise buyers.
• Andela: Global talent marketplace that places vetted senior engineers into client engineering teams, with a comparable staff-augmentation and embedded-pod value proposition, particularly for AI and product engineering roles.
• Turing: AI/engineering services platform that matches vetted senior engineers with enterprise and AI-native clients, with comparable pricing (per-engineer monthly) and a similar focus on production-grade AI delivery.
• SoftServe: Digital engineering services firm with a large AI/ML practice offering embedded teams and end-to-end product delivery across healthcare, fintech, and SaaS — directly comparable in delivery model and vertical mix.
• Itransition: Custom software development firm providing AI engineering, full-stack development, and QA services with embedded team delivery, comparable to Procedure's pod-based model and multi-vertical solution set.

Broad incumbents

• Genpact: Large digital transformation services firm with AI engineering capabilities spanning financial services and healthcare; broader portfolio but overlapping buyer segments and comparable enterprise-scale delivery.
• Accenture: Global systems integrator with a large AI engineering practice and enterprise sales motion; not a direct boutique competitor but competes for the same enterprise AI deployment budgets and outcome-based engagements.

Emerging players

• Xoriant: Product engineering and AI/ML services firm offering embedded teams and AI application development for fintech, healthcare, and SaaS buyers — overlapping in delivery model and target verticals at a comparable scale.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat4 records

Key risks6 records

Key highlights7 records

Customer concentration

• Xx.com/ProcedureHQ
• LinkedInlinkedin.com/company/procedure-technologies
• GitHubgithub.com/procedure

Revenue estimate

Valuation estimate

Number of profiles

Profiles2 records

Funding overview

Funding rounds

Investors

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about Procedure Technologies