Independent AI & data engineering ·
Koblenz, Germany
Empyron Solutions builds production AI systems for growing teams: MCP-connected agents, hybrid RAG, fine-tuned LLMs, and the data pipelines that make them useful.
Direct access to the engineer designing and building your system.
SYSTEM MAP / 01
INPUTS
Documents
Business data
ENGINEERING
MCP tools
Hybrid RAG
Fine-tuned model
IN USE
Grounded answers
Approved actions
The right system depends on the problem, the data, and where it needs to run.
What we build
We work across the full stack: connect models to tools, retrieve the right context, adapt models when needed, and ship the software around them.
Tell us what you're solvingAgents that call the right tools, use your systems, and hand off sensitive actions for approval. We build MCP clients and servers around real business workflows.
MCP · OpenAI Agents SDK · LangGraph · tool calling · human approval
Ground answers in your documents with semantic and keyword retrieval, metadata filters, reranking, citations, and evaluation against real queries.
Dense vectors · BM25 · RRF · rerankers · retrieval evaluation
Adapt open-weight models when prompting is not enough. We prepare datasets, fine-tune adapters, measure quality, and package models for the target hardware.
Hugging Face PEFT · TRL · LoRA · QLoRA · quantization
Put hosted or self-hosted models behind reliable APIs, connect them to products, and tune inference for latency, privacy, and cost.
OpenAI & Anthropic APIs · vLLM · SGLang · FastAPI
Build the pipelines and workflow automation around AI: forecasting, classification, integrations, and the operational data foundations that keep systems useful.
Python · PostgreSQL · Redis · Docker · n8n · predictive ML
Experience across
Technology stack
From MCP and agent orchestration through hybrid search, fine-tuning, and inference. We choose the smallest stack that meets your data, privacy, latency, and cost requirements.
Connect models to business tools, APIs, and data with controlled, observable workflows.
Combine semantic and exact-match search, fuse results, then rerank for relevance.
Adapt open-weight models with parameter-efficient training, task-specific evaluation, and quantized delivery.
Run models through hosted APIs or self-hosted serving, integrated with production data and software.
Technology examples, not a fixed bill of materials. Model, framework, and hosting choices are scoped to each project.
Selected work
A few examples of the work Empyron has delivered across legal, e-commerce, and SaaS teams. Client names are omitted here.
Legal · Document intelligence
A retrieval system for a German legal practice, built to search case files and contracts in natural language and return answers with citations.
LangChain · ChromaDB · Hetzner VPS
2,000+
case files made searchable
Searches that took an afternoon now take seconds.
E-commerce · Operations
n8n workflows for a Shopify brand handling 200+ orders a day, covering order validation, customer-notification triage, and inventory alerts.
n8n · LLM integrations · Shopify
80%
of manual operations tasks automated
Order validation, notification triage, and inventory alerts.
E-commerce · Generative imagery
A Stable Diffusion XL model fine-tuned on a fashion catalogue, delivered through a lightweight app for the client team.
Stable Diffusion XL · Gradio
60%
lower photoshoot costs
On-brand imagery generated from simple flat-lay photos.
SaaS · In-product assistant
A fine-tuned Phi-3-mini assistant using product support material, quantized to run under 2 GB of VRAM for low-cost inference.
Phi-3-mini · 4-bit quantization
70%
of Tier-1 queries handled without escalation
A fine-tuned assistant deployed for a SaaS support workflow.
How we work
The work is collaborative: we agree on the problem and scope first, then show progress as the system takes shape.
Start a conversationA free 30-minute call to understand the workflow, the data, and what a useful outcome would look like.
First conversation
We define the deliverables, timeline, assumptions, and written scope before any build begins.
Usually 2–3 days
Short feedback cycles and regular demos keep the build aligned with the problem you need solved.
Often 2–8 weeks
We ship with documentation and a practical handoff, then agree what support makes sense for the system.
Support by agreement
Bhavya Shah
Founder · Principal Engineer
About Empyron
Empyron Solutions is an independent AI and data engineering studio founded by Bhavya Shah. We work directly with startups and small businesses to solve practical problems with data, machine learning, and language models.
Before starting Empyron in 2024, Bhavya built production AI systems in enterprise settings. Today, he stays involved from the first scoping conversation through implementation and handoff — so the engineering stays connected to the problem.
Contact
Share a little context about the problem, the data, and what a good outcome would look like. We'll reply to discuss whether and how we can help.
bhavya@empyronsolutions.comBased in Koblenz, Germany · Available for remote work across Europe and India.