AI agents & LLM automation
Replace manual review and rule-based processes with LLM workflows that are measured, monitored and cheap to run. We start with the step where people spend the most time.
- agentic workflows
- RAG
- web extraction
- evaluation
AI & data engineering consulting
StratumMeta designs, builds and modernizes the full technology stack: data platforms and pipelines, distributed processing at petabyte scale, cloud architecture on AWS, Google Cloud and Azure, and the AI agents and LLM systems on top. We bring decades of engineering leadership, and we stay hands-on from first prototype to production.
a year in infrastructure savings from a legacy-to-cloud migration
of a manual review workload automated with LLMs
a month cut from cloud spend by re-architecting data pipelines
scale data platforms processing billions of records
Four engagements we take on, from a scoped build to ongoing leadership. Each one ends with a working system your team can own.
Replace manual review and rule-based processes with LLM workflows that are measured, monitored and cheap to run. We start with the step where people spend the most time.
Design or rebuild the pipelines that feed your models and products, sized for the data you will have in two years.
Move legacy on-prem systems to cloud-native architecture, then tune them: spot capacity, right-sized processing units, job prioritization and restart.
Senior leadership for a team that needs direction: roadmap, architecture reviews, hiring and mentoring, and a clear path from proof of concept to production.
Short cycles, real data from the first week, and a handoff plan from the start.
Map the process, the data and the costs. Pick the one change with the clearest payoff.
A working proof of concept on your data in weeks, with an agreed measure of success.
Develop the full solution in short sprints: data pipelines, models and agents, APIs and integrations, with a working demo every two weeks.
Deploy and harden it: scale, monitoring, cost controls, security and failure recovery.
Documentation, training and pairing so your engineers run it without us.
Drawn from programs our founders have led in data-intensive industries.
AI agents · automation
Find the repetitive verification, research and triage work your team does by hand, and build AI agents that take it over, with people approving the edge cases. Each agent is measured against your team's accuracy before it goes live.
AI agents · LLM workflows · human-in-the-loop
Enterprise knowledge · RAG
Connect LLMs to your internal documents, databases and systems with retrieval-augmented generation. Teams get grounded answers with sources, instead of searching across a dozen tools.
RAG · semantic search · embeddings
Data quality · LLMs
Transition from manual rule-based systems to intelligent, automated data processing pipelines, unified data structures, and continuous quality control. Modernize ingestion frameworks to process complex, multi-source enterprise data, driving significant expansions in coverage while optimizing operational efficiency.
LLMs · semantic embeddings · agents
Cloud modernization
Migrate high-volume legacy infrastructure to modern, cloud-native architectures. Re-engineer data pipelines with dynamic resource allocation, automated fault tolerance, and scalable capacity, substantially reducing operational run costs while ensuring system reliability and continuity. The result is an AI-ready data foundation for your models and agents.
Spark · serverless · cost controls · AI-ready data
Large-scale analytics
Architect high-throughput distributed architectures to process high-velocity data streams across diverse operational touchpoints. Apply machine learning models to detect system anomalies and refine data quality in real time, delivering actionable intelligence across core business applications.
machine learning · clustering · geospatial · distributed processing
Commerce & finance
Build mission-critical digital platforms, transactional systems, ML-driven recommendations and AI-automated enterprise workflows. Engineered for high-concurrency environments, zero-downtime reliability, and adherence to strict regulatory standards.
ML recommendations · payments · AI workflow automation
About the founders
StratumMeta's founders are engineering leaders and patent-holding technologists. They have run global engineering organizations, delivered multi-million-dollar cloud savings, and teach data engineering and AI at the university level.
They combine strategic leadership with deep technical work in cloud, data and AI. They set the roadmap, upskill your team and write production code alongside your developers, taking a project from first prototype to enterprise scale.
The senior leaders who design your solution are the ones who deploy it.
Tell us what you are working on. We reply within one business day and can usually scope a first step in a single call.