PRODUCTION-GRADE AI ENGINEERING
Build AI Systems That Ship
Real-world AI needs engineering beyond vibe-coding.
We build systems that scale and stand the test of time.
Most AI projects fail silently
And it's not because of the models
Demos don't scale
That impressive POC? It breaks under real load. Technical debt compounds. Costs spiral.
Mistakes surface late
Architectural decisions made in week 1 become million-dollar problems at scale.
Projects never end
Unlike traditional software, AI can consume resources indefinitely with no clear ROI.
Our Mindset
AI requires a different approach than traditional software
Rapid Experimentation Without Ceremony
AI outcomes are uncertain. We iterate quickly to discover what works.
Technical Depth That Prevents Expensive Mistakes
AI systems can fail in costly ways. We identify risks before they become six figure problems.
Honesty to Kill Ideas That Don't Work
Unlike traditional software, AI projects can consume resources indefinitely. We know when to stop.
Adaptive Planning That Embraces Uncertainty
AI capabilities evolve monthly. Fixed plans become outdated quickly. We stay nimble.
The Unravel Difference
Technical depth meets practical engineering
Production AI Engineering
Building AI systems that work reliably in production, not just in notebooks. We handle the edge cases, failure modes, and scale challenges that demos ignore.
Robust Distributed Systems
Enterprise-scale infrastructure that handles complexity. Real observability, real monitoring, real resilience.
Delightful Product Engineering
Making powerful systems feel simple to use. Because the best AI is invisible. It just works.
How We Work
Four stages from assessment to production
Strategic Assessment
Identify & Prioritize
- Evaluate current state and AI maturity
- Map opportunities to business impact
- Design POC roadmap with clear success criteria
Rapid Prototyping
Validate & Learn
- Build lightweight experiments
- Test core assumptions quickly
- Iterate based on real user feedback
Technical Architecture
Design & De-Risk
- Assess feasibility and approaches
- Identify risks before they're expensive
- Establish observability frameworks
Production Engineering
Scale & Optimize
- Deploy robust, production-grade systems
- Monitor, measure, continuously improve
- Adapt based on actual performance
Proven Results
Real deployments, real outcomes
The Unravel team embodies a unique combination of leaders and hackers. They are seasoned developers and their work-product is fast, reliable and delightful!
Unravel built our complete event-ingestion pipeline. Their distributed systems expertise let me focus on business outcomes—a partnership we'll gladly continue.
Multi-Agent Orchestration for HNI Clients
Research agent that handles routine client queries, freeing advisors to focus on high-value strategic work. Became the most requested premium feature.
Autonomous Sales Intelligence Agents
Transforms hours of research into instant intelligence. Pilots receiving "rave reviews" from account executives.
Advanced AI Capabilities
Production-tested techniques that power intelligent systems
Memory
Long-term and short-term memory systems that allow agents to learn from interactions and maintain context across sessions.
MCP
Model Context Protocol for standardized communication between AI models and external tools, enabling seamless integrations.
Multi-Agent Orchestration
Coordinate multiple specialized agents working together to solve complex tasks that require diverse expertise.
Knowledge Graph
Structured knowledge representations that capture relationships between entities for enhanced reasoning and retrieval.
Agentic State
Persistent state management that enables agents to track progress, maintain workflows, and resume interrupted tasks.
Agentic RAG
Retrieval-Augmented Generation with autonomous decision-making about when and how to fetch relevant information.
Context Engineering
Optimize prompt context windows with strategic information selection, compression, and hierarchical structuring.
Research Agents
Autonomous agents that conduct multi-step research, synthesize findings, and generate comprehensive reports.
Evaluations
Rigorous testing frameworks for AI outputs using automated metrics, human feedback, and continuous monitoring.
Structured Input & Output
Enforce type-safe schemas for AI interactions ensuring reliable, parseable responses that integrate seamlessly.
Enterprise-Grade Stack
Production-tested tools that power scalable AI systems
LLM Frameworks & Orchestration
Observability & Evaluation
Databases & Vector Stores
Deployment & Infrastructure
Models & Inference
Open Source
We contribute to the AI/ML ecosystem
Let's assess your AI opportunity
No pitch decks. No lengthy proposals. Just an honest conversation about what's possible and what isn't.