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KMM Technologies, Inc. Tech Stack

AI transformation and enterprise platform integration for regulated industries

IT Services and IT Consulting Rockville, Maryland 201–500 employees Founded 2003 Privately Held
kmmtech.ai LinkedIn

KMM Technologies builds AI and cloud modernization practices for financial services, insurance, healthcare, and government. The stack is heavily AWS-native (Lambda, EMR, Glue, RDS, DynamoDB) with Python and Apache Spark for data pipelines, plus ARIS and Informatica for enterprise architecture and data integration—a pattern typical of consulting shops serving large regulated organizations. Hiring is engineering-focused (10 of 17 roles) at senior and lead levels, and the project list centers on MLOps governance, cloud-native reference architectures, and end-to-end AI/ML solutions, indicating a shift from legacy modernization toward repeatable AI delivery models.

Tech Stack 152 technologies

Core StackInformatica Python Terraform GitLab Ansible AWS CloudFormation AWS Lambda Apache Spark Hadoop PySpark AWS Glue FastAPI Flask React Angular Vue AWS RDS DynamoDB Docker ARIS Unix Shell AWS Systems Manager AWS CloudWatch Amazon EMR AWS ECS API Gateway AWS Application Load Balancer Batch EFS+120 more

What KMM Technologies, Inc. Is Building

◆Challenges

  • Provider data accuracy issues
  • Speed-to-market improvement
  • Marketing process inefficiencies
  • Architecture as documentation
  • Scaling cloud-native applications
  • Reliability of distributed systems
  • Scaling mlops to enterprise scale
  • Ensuring secure, compliant ml governance
  • Claims platform integration
  • Complex multifamily business processes

▲Active Projects

  • Marketing business architecture roadmap
  • Marketing platform governance
  • Application portfolio management
  • Technology portfolio management
  • Modernization scorecard
  • End-to-end ai/ml and generative ai solutions
  • Cloud-native applications on aws
  • Mlops workflows
  • Enterprise mlops architecture across full ml lifecycle
  • Cloud-native reference architectures on aws for ml platforms

Hiring Activity

Accelerating15 roles · 15 in 30d

Department

Engineering
10
Data
2
Healthcare
1
Marketing
1
Ops
1
Product
1

Seniority

Senior
11
Mid
3
Junior
1
Lead
1
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About KMM Technologies, Inc.

KMM Technologies is a 20-year-old consulting and implementation firm headquartered in Rockville, Maryland, serving mid-market to enterprise clients across financial services, insurance, healthcare, media, retail, and public sector (federal and state government). The company combines strategy, intelligent automation, and enterprise platform integration—delivering custom AI implementations, cloud migrations to AWS, and MLOps infrastructure. ISO 27001, CMMI Level 2, and ISO 9001 certified. Currently operating at 201–500 employees with active hiring in the United States, India, and Canada.

HeadquartersRockville, Maryland
Company Size201–500 employees
Founded2003
Hiring MarketsUnited States, India, Canada

Frequently Asked Questions

What tech stack does KMM Technologies use?

AWS-native (Lambda, EMR, Glue, RDS, DynamoDB, ECS, CloudFormation), Python, Apache Spark, FastAPI, React/Angular/Vue frontends, Terraform for infrastructure-as-code, GitLab for CI/CD, Ansible for orchestration, Docker containerization, plus ARIS and Informatica for enterprise architecture and data integration.

What is KMM Technologies working on?

Enterprise MLOps architecture, cloud-native ML platforms on AWS, end-to-end AI/ML and generative AI solutions, application and technology portfolio management, modernization scorecards, and marketing platform governance for regulated industries.

How this profile is built

KMM Technologies, Inc.'s technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →

This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.