AI Consulting · Agentic Workflows · Prompt Engineering
AI consulting and agentic workflow engineering for companies that need it to actually work.
Optraject is an AI engineering consultancy that helps companies introduce AI, design agentic workflows and build production-grade AI agents and LLM integrations — using Claude, the OpenAI API, MCP (Model Context Protocol), RAG and vector databases — backed by 20+ years of enterprise software engineering experience.
Two focus areas inside AI Engineering
Most engagements fall into one of two categories — getting an LLM to reliably do what you need, or getting an AI agent to reliably act on your behalf. We do both, often together.
Focus area
Prompt Engineering & LLM Optimization
System-prompt design, evaluation and testing, retrieval-augmented generation (RAG) and the discipline of getting consistent, production-safe output from Claude and OpenAI models.
Prompt engineering services →
Focus area
AI Agents & Agentic Workflows
Multi-step AI agents that plan, call tools and act — built with LangGraph and MCP, with guardrails and human-in-the-loop checkpoints where control matters.
AI agent development →
What does AI engineering with Optraject include?
A full path from "should we do this?" to a system running in production — not an isolated deliverable.
01
AI readiness & strategy assessment
We map your workflows, data and systems to find the use cases where AI creates measurable value first — honestly, including where it doesn't.
02
LLM & API integration
Integrating Claude, OpenAI API, Azure OpenAI or AWS Bedrock into your applications, with RAG pipelines and vector databases where grounded, up-to-date answers matter.
03
Agentic workflow design
Multi-agent systems orchestrated with LangGraph and connected to your tools and data via MCP — designed for control, not just capability.
04
Prompt engineering
System prompts, tool definitions and evaluation harnesses engineered and tested like software — not tuned by trial and error.
05
AI-assisted engineering enablement
Helping your own development team adopt AI-assisted workflows — tools like Claude Code — to ship faster without sacrificing code quality.
06
PoC to production
A proof of concept in 2-6 weeks against real data, then hardening for production: security, monitoring, governance and integration into your landscape.
Which technologies power these projects?
We are model- and cloud-agnostic by design, and pick the stack that fits your existing infrastructure and risk profile.
Claude & OpenAI API
Foundation models for reasoning, generation and tool use, chosen per use case.
MCP (Model Context Protocol)
The open standard we use to connect models and agents to your tools, data and systems safely.
RAG & vector databases
Retrieval-augmented generation grounded in your own documents and data, reducing hallucination risk.
LangGraph orchestration
Multi-agent orchestration with explicit state, retries and control flow — not black-box chains.
Azure OpenAI
For organizations standardized on Microsoft's cloud and compliance posture.
AWS Bedrock
Managed model access and guardrails for teams already running on AWS.
Claude Code
AI-assisted development workflows we use ourselves — and help your team adopt.
Enterprise integration
APIs, message queues and legacy systems — connected, not replaced, wherever possible.
How does an AI engagement typically proceed?
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Step 1
Assess
A short readiness assessment identifies the highest-value use case and the data and systems it needs to touch.
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Step 2
Pilot
A proof of concept in 2-6 weeks: a working agent or LLM integration against real data, evaluated against clear success criteria.
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Step 3
Productionize
We harden the solution — security, monitoring, guardrails, governance — and integrate it into your systems and team.
AI with enterprise discipline
An AI agent is only as good as the system it runs in. Optraject pairs every AI engagement with the same architecture and engineering discipline we have applied for global automotive manufacturers, insurance groups and technology corporations for over 20 years — secure integration, maintainable code, and infrastructure that scales past the pilot.
Explore Software Architecture & Development →Frequently asked questions
What does an AI consulting engagement with Optraject look like?
It starts with a short readiness assessment to identify high-value use cases, moves into a focused proof of concept within 2-6 weeks against real data, and — once validated — into production engineering with security, monitoring and governance built in. No slideware, no year-long strategy phases.
What is agentic AI, and how is it different from a chatbot?
A chatbot answers questions in a conversation. Agentic AI goes further: an AI agent plans multi-step tasks, calls tools and APIs, retrieves data, and takes actions toward a goal with minimal human prompting at each step. Optraject designs agentic workflows using frameworks like LangGraph and the Model Context Protocol (MCP), with human-in-the-loop checkpoints where needed.
Should we build our own AI solution or buy an off-the-shelf tool?
It depends on how core the workflow is to your competitive advantage. Off-the-shelf tools are faster for generic tasks; custom agentic workflows and LLM integrations pay off when the process is specific to your business, your data or your systems. Optraject helps you make that call honestly, then builds only what's worth building.
How long does an AI proof of concept take?
Typically 2-6 weeks for a focused proof of concept against real data and a clear success metric. Complexity, data access and integration requirements affect the timeline, but the goal is always evidence within weeks, not a multi-month strategy exercise.
Which AI models and technologies does Optraject work with?
We work with Claude, the OpenAI API, Azure OpenAI and AWS Bedrock, and build retrieval-augmented generation (RAG) pipelines with vector databases. For agent orchestration we use frameworks such as LangGraph and the Model Context Protocol (MCP) to connect models to tools, data and enterprise systems.
How is Optraject different from other AI consultancies?
Engineering depth. Most AI consultancies hand over strategy decks; Optraject has delivered enterprise software for global automotive manufacturers, insurance groups and technology corporations for over 20 years, and applies that same production discipline — security, testing, maintainability — to every AI engagement.
Can Optraject help our existing development team adopt AI-assisted engineering?
Yes. Beyond building AI products, we help engineering teams adopt AI-assisted development practices — tools like Claude Code, code-review agents and workflow automation — so your own developers ship faster without sacrificing quality.
Does introducing AI mean rebuilding our existing systems?
Rarely. Most AI initiatives succeed by integrating into what already exists — connecting LLMs and agents to your current databases, APIs and legacy systems via well-designed interfaces such as MCP, rather than a full rewrite. Optraject designs AI-ready architecture on top of what you already run; see our software architecture services for the enterprise-side discipline behind this.
Ready to introduce AI that actually ships?
Tell us about your workflow or challenge — we'll reply with an honest, concrete assessment of where AI can help.
Contact us