Case studies
End-to-end RAG
for an online DJ school
Crossfader
We helped Crossfader transform its extensive library of DJ courses and articles into an AI-powered semantic search and learning assistant. We designed and deployed an end-to-end RAG system using Qdrant, OpenAI, FastAPI, and AWS, enabling users to receive fast, context-aware answers grounded in Crossfader’s proprietary educational content.
We helped Crossfader transform its extensive library of DJ courses and articles into an AI-powered semantic search and learning assistant.
We designed and deployed an end-to-end RAG system using Qdrant, OpenAI, FastAPI, and AWS, enabling users to receive fast, context-aware answers grounded in Crossfader’s proprietary educational content.
We helped Crossfader transform its extensive library of DJ courses and articles into an AI-powered semantic search and learning assistant. We designed and deployed an end-to-end RAG system using Qdrant, OpenAI, FastAPI, and AWS, enabling users to receive fast, context-aware answers grounded in Crossfader’s proprietary educational content.
AI Agent integration into an existing production software framework
Simplica
Collapsible text is perfect for longer content like paragraphs and descriptions. It's a great way to give people more information while keeping your layout clean. Link your text to anything, including an external website or a different page. You can set your text box to expand and collapse when people click, so they can read more or less info.
We designed and implemented Simplica’s agentic AI foundation, including a multi-agent architecture, evaluation framework, guardrails, fine-tuning pipelines, and experimentation infrastructure.
The system combines OpenAI agents SDK, custom evaluators, structured prompt orchestration, and tool-based agents to enable creation and execution of application within this framework.
We designed and implemented Simplica’s agentic AI foundation, including a multi-agent architecture, evaluation framework, guardrails, fine-tuning pipelines, and experimentation infrastructure.
The system combines OpenAI agents SDK, custom evaluators, structured prompt orchestration, and tool-based agents to enable creation and execution of application within this framework.
Agentic Order Validation
System for E-commerce Platform
Siemens Energy
Collapsible text is perfect for longer content like paragraphs and descriptions. It's a great way to give people more information while keeping your layout clean. Link your text to anything, including an external website or a different page. You can set your text box to expand and collapse when people click, so they can read more or less info.
Add paragraph text. Click “Edit Text” to update the font, size and more. To change and reuse text themes, go to Site Styles.
Add paragraph text. Click “Edit Text” to update the font, size and more. To change and reuse text themes, go to Site Styles.
We designed and implemented a multi-agent order validation system for Siemens Energy that automated the verification and traceability of high-value industrial orders. Processes previously handled through lengthy manual reviews could now be validated before execution with greater speed, consistency, and reliability.
Our Solutions for Your Specific Needs
Our Services
AI Agents, Built for Your Product & Processes
AI agents can take over real, multi-step work, not just answer questions. For instance, a well-built agentic system can pick up a ticket, query your database, write the code, test it and deploy it to the cloud. Or it can triage incoming support tickets, pull customer history from your CRM, draft a response, and escalate the ones that need a human.
Calibrion designs and builds these agentic workflows for your specific use case. We we design and build agents and their tools, integrate them with your systems — databases, CI/CD, internal APIs, web UIs, MCP servers — and ship it to production with the evaluations and feedback loops it needs to keep working over time.
RAG Systems That Ground AI in Your Data
RAG (Retrieval Augmented Generation) enables AI answer from your actual content (your docs, content, tickets, codebase, product data, etc.) instead of guessing. It cuts hallucinations and keeps answers current as your data changes.
But implementing RAG effectively is often challenging, especially with fragmented knowledge sources, weak retrieval quality, poor chunking, missing metadata, and infrastructure that is not set up for reliable search. At Calibrion, we design and implement RAG solutions tailored to your product, data, and infrastructure, using the right architecture, databases, and retrieval methods for durable performance.
Custom Evaluators for Reliable Agents
One of the biggest bottlenecks in putting AI agents into production is knowing whether they're actually doing a good job. Without a clear way to measure quality, teams end up shipping agents they can't fully trust, catching problems only after users hit them, and making changes without knowing if things are getting better or worse. That's where evaluation comes in.
Calibrion designs and implements evaluation systems tailored to your product, domain, and risk profile. Backed by years of applied AI experience and deep expertise in LLMs, ML, and evaluation methods, we build evaluators that help you measure performance with clarity, whether through statistical methods, domain-specific ML evaluators, LLM-as-a-judge, or multi-judge LLM juries.
Synthetic Data Generation
Manual data labeling is slow, expensive, and rarely covers the edge cases your AI actually fails on. Synthetic data generation can close that gap — producing training and evaluation data at scale, including the rare cases real datasets miss.
Calibrion designs synthetic data pipelines for your specific use case, whether you need training data for a new model, eval sets that stress-test edge cases, or privacy-safe data for testing. We pick the right generation method, build in quality controls so the data is actually useful, and integrate the pipeline with your training and evaluation workflows.
Model Customization
Fine-tuning can unlock much stronger performance for your specific use case, but doing it well is rarely straightforward. It requires the right data, careful experimentation, thoughtful model selection, strong evaluation, and clear decisions around privacy and IP.
At Calibrion, we help you customize LLMs for your product and domain so the result is not just more specialized, but more reliable and aligned with your business needs.
Advise & Strategy
Most AI initiatives fail not because the technology doesn't work, but because teams pick the wrong problem, choose the wrong architecture, or build something they can't reliably operate.
Calibrion advises product and engineering leaders from the practitioner's seat not from slides. We help you decide what to build (and what not to), choose the right architecture and stack, scope realistic timelines, and avoid the failure modes we've seen kill AI projects. Engagements range from a focused opportunity audit to ongoing technical advisory through implementation.