Depend on proven experts

We know how to solve your business problems using AI. And we know how to scale it up.

We've processed a quarter billion dollars in revenue at scale with nearly 100% uptime. We've built production RLHF systems that transform core business processes through self-evolving AI agents. We don't just talk about AI—we deliver it at scale.

Our Mission

Deliver serverless business solutions using collaboration between human and artificial intelligence in every aspect of development and operations.

Our Values

Prioritize Solutions Over Tools
Investing in products and services only delivers business value if you're in the business of products and services. We're in the business of solutions.
Design for Humans
Computers exist to help humans accomplish things. Not the other way around. Make it easy for the human, not the computer.
Focus on Business Logic
The only code you should be writing is the business logic that solves real problems. Don't waste time reinventing wheels.
Continuously Improve
Enable rapid, iterative change through CI/CD and DevOps for code, and RLHF and MLOps for AI/ML. Mitigate the risk of making changes by deploying lots of small, verifiable steps.
Collaborate with AI Humanely
People skills are vital for leveraging artificial people. You can get a lot more out of AI tools if you know how to collaborate with people.
Implement Infrastructure as Code
Leverage DevOps to implement Infrastructure as Code. Every aspect of a production system should be created and configured by code so that it's reproducible, not manually.
Commodify AI Models
Treat AI models as replaceable, not magic black boxes. In a world with no moats, don't invest too much in any given castle.
Optimize Resource Usage
Balance efficiency with cost-effectiveness so that your idea will be sustainable and so that it can scale.

Our Capabilities

Smart Process Automation
Delegate routine tasks to intelligent systems, freeing your team for higher-impact initiatives.
AI-powered software features.
Infuse AI-driven capabilities into your cloud-based apps, mobile applications, or existing systems.
Serverless software solutions.
Not all AI-enabled solutions use AI at runtime. We have a long and proven history of building serverless architectures that deliver business value.
Conversational AI Agents
Elevate your efficiency by integrating a conversational AI co-pilot, enabling dialogues with your business operations.

Production MLOps at Scale

Plexus: The RLHF Data Flywheel

We built what many consider the holy grail of AI: a production-scale RLHF system that continuously aligns itself with human feedback automatically over time. Plexus is our custom MLOps platform that powers this self-evolving data flywheel, managing the complete lifecycle of AI agents and classification models that get smarter with every interaction.

Two years of continuous production operation
Self-evolving AI agents that improve autonomously
Human-in-the-loop feedback drives continuous learning
Transforms core business processes at scale

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Featured Solutions

Speaker Role Classifier

November 2025

A real-world example of how the agentic programming paradigm enables rapid solution development. We faced a problem where ambiguity in speaker role names could have made a traditional programmatic solution complex and time-consuming. By giving an AI agent the right tools, we delivered a working solution quickly and moved on—demonstrating how agent-based programming enables much greater agility and speed. View the project on GitHub.

Classification with Confidence

September 2025

A practical exploration of LLM fine-tuning for text classification. By fine-tuning GPT-4o-mini, we significantly improved classification accuracy and alignment to specific business requirements. The project demonstrates a production-ready approach to model alignment with confidence scoring that determines when human review is needed—a practical application of human-in-the-loop principles that balances automation with expert oversight. View the project on GitHub.

SQLBot: Your AI Database Analyst

September 2025

SQLBot is a new kind of interface for your database. Instead of writing SQL queries yourself, you delegate high-level analytical tasks to an AI agent. It reasons through your request, executing a chain of queries and analyzing the results until it arrives at a complete answer—all while keeping your data safe with built-in safeguards. View the project on GitHub.

Call Criteria

October 2023 - ongoing

We transformed a call center QA company by converting human-led processes into cybernetic systems that blend AI with human expertise. This groundbreaking work led to the development of Plexus, our enterprise AI platform. The results: unprecedented scalability with costs reduced by orders of magnitude, AI call reviews that outperform human reviews in speed and consistency, and automated AI setup for new client scorecards that streamlined onboarding. Our solution solved immediate challenges while opening new avenues for continuous improvement in call center quality assurance, ultimately evolving into a comprehensive enterprise AI platform.

View all our Solutions.

Recent Articles

AWS Lambda for AI/ML

2025-11-22

Serverless isn't just for web apps anymore. Here's how we use the "Serverless AI Stack"—Lambda for orchestration, AgentCore for agents, and SageMaker Serverless for inference—to build production AI systems that scale to zero.

The Turn Detection Trap: When 100% Accuracy is Wrong

2025-11-22

We fine-tuned MobileBERT for turn detection and achieved 100% accuracy. Then we realized we hadn't solved turn detection at all—we had just built a very expensive punctuation detector.

Give an Agent a Tool

2025-09-15

A demonstration of a fundamental paradigm shift in computer programming: from writing explicit code for every scenario to giving intelligent agents the right tools and letting them figure it out. This project shows how the same task that requires hundreds of lines of complex branching logic in traditional programming becomes simple and flexible with agentic AI. Through a real-world example of extracting contacts from varied CSV formats, we compare traditional approaches against agent-based data processing that handles unexpected formats without code changes, demonstrating the 'give an agent a tool' paradigm in action. View the project on GitHub.