Fortune 100 Technology Company
Enterprise Knowledge Agent
A stateful agent architecture connecting enterprise knowledge, tools, and approval workflows.
Independent AI Engineering
We build AI systems
that work in the real world.
Enterprise AI, machine learning, and agentic systems — designed, built, and deployed by experienced engineering teams.
Platforms our teams work with
- OpenAI
- Anthropic
- Google Cloud
- AWS
- Microsoft Azure
02 / Positioning
We work where AI meets real engineering.
Agentic Systems
Autonomous and human-in-the-loop systems that reason, use tools, maintain state, and complete multi-step work.
Enterprise AI
AI systems grounded in enterprise context, permissions, workflows, and business knowledge.
Machine Learning
Production ML systems spanning data, modeling, inference, deployment, and evaluation.
AI Platforms
Shared infrastructure for model access, retrieval, orchestration, observability, and governance.
03 / Capabilities
From model to production.
Agent Architecture
Multi-step agents with defined planning, tool use, and approval boundaries.
RAG & Enterprise Search
Retrieval grounded in internal knowledge and enforced at the permissions layer.
LLM Applications
Production interfaces to language models, built for real usage patterns.
Model Evaluation
Evaluation harnesses that gate releases on measured output quality.
ML Engineering
Model development and inference systems built to run in production.
AI Infrastructure
Shared platform infrastructure for model access, routing, and scaling.
Data & Retrieval
Data and indexing pipelines that keep retrieval accurate as content changes.
MLOps
Deployment, monitoring, and versioning for models running in production.
AI Observability
Tracing and monitoring across every model call, agent step, and tool use.
Multimodal AI
Systems that reason across text, images, and structured data together.
Enterprise Integrations
AI systems connected directly into the tools a business already runs on.
AI Security
Security review and controls built for systems that take autonomous action.
04 / Selected Work
Selected work
Global Enterprise Software Company
Intelligent Document Platform
A production document-understanding pipeline spanning extraction, classification, and review.
Leading Financial Platform
AI Operations Platform
Shared infrastructure for model access, evaluation, and observability across internal AI systems.
Enterprise SaaS Platform
Adaptive Support Copilot
A support copilot grounded in product documentation, account context, and prior resolutions.
05 / How We Work
Built like an engineering team, not a consultancy.
Understand
Identify the business problem, system constraints, data environment, and measurable outcome.
Architect
Define system boundaries, model strategy, retrieval design, data architecture, and production constraints.
Build
Implement production systems directly with client product and engineering teams.
Operate
Evaluate, observe, improve, and harden systems after launch.
06 / AI Lab
Exploring what comes after today's AI stack.
Alongside client work, our teams build experimental systems around autonomous agents, long-running AI workflows, machine reasoning, and next-generation AI infrastructure.
Prototype
Persistent Agents
Agents that maintain progress and state across long-running workflows, restarts, and human approvals.
Research
Adaptive Retrieval
Retrieval systems that dynamically select context based on user, task, and model behavior.
Active
Agent Evaluation
Infrastructure for measuring tool use, reliability, trajectory quality, and long-horizon completion.
07 / Technology Ecosystem
Platforms we build on.
- OpenAI
- Anthropic
- Meta
- AWS
- Azure
- Google Cloud
- Kubernetes
- Ray
- PyTorch
- LangGraph
- MLflow
- Databricks
- PostgreSQL
- Snowflake
- Elasticsearch
- Pinecone
- Redis
Careers
Build what's next.
We're looking for engineers who want to work on difficult AI problems that matter in production.