What types of AI systems does Oronts build?

Our AI development services cover agentic AI systems, RAG pipelines, LLM integration, AI workflow automation, business automation, and AI observability platforms. On the agentic side, we build multi-agent orchestration systems where specialized agents handle tasks like document analysis, customer support triage, and data extraction, coordinated through frameworks like Mastra AI or LangGraph. Our RAG pipelines combine vector databases such as Pinecone or Weaviate with embedding models to give LLMs access to your proprietary data without fine-tuning. For workflow automation, we connect AI capabilities to existing business processes through API integrations, turning manual review steps into AI-assisted decisions with human oversight. Every system we ship includes evaluation harnesses, latency monitoring, and cost tracking dashboards so you can measure accuracy, performance, and spend from day one. Our solutions are production-ready and designed for enterprise-scale deployment with proper error handling and graceful degradation.

How does Oronts ensure AI system reliability in production?

We implement comprehensive AI observability including model monitoring, evaluation pipelines, drift detection, and automated alerting. On the monitoring side, we track inference latency, token usage, error rates, and output quality scores through Grafana dashboards that your team can access in real time. Our evaluation pipelines run automated test suites against golden datasets before any model update reaches production, catching regressions before users see them. Drift detection compares current model outputs against baseline distributions and flags statistical deviations that could indicate degraded performance due to changing input patterns. Every system includes fallback mechanisms and human-in-the-loop safeguards. For example, if an AI classification confidence score falls below a defined threshold, the system automatically routes the decision to a human reviewer instead of proceeding with a low-confidence prediction. We also implement circuit breakers that switch to rule-based fallbacks if the model endpoint becomes unavailable, ensuring your business processes never stall completely.

Can Oronts integrate AI into our existing enterprise systems?

Yes. We specialize in LLM integration and AI automation within existing enterprise infrastructure including ERP, CRM, and custom platforms. Rather than replacing your current systems, we add AI capabilities alongside them through well-defined API boundaries. For example, we can connect an LLM-powered document processor to your SAP workflow so purchase orders are automatically extracted, validated against master data, and routed for approval without changing your existing approval chain. For CRM integrations, we build AI agents that summarize customer interaction history, suggest next actions, and auto-draft follow-up emails directly within Salesforce or HubSpot. Our approach ensures minimal disruption while delivering measurable business automation gains. We typically start with a single high-impact use case, measure the results over 4-6 weeks, and then expand to additional workflows based on proven ROI. This incremental strategy reduces risk and builds internal confidence in AI-assisted processes across your organization.

What AI frameworks and models does Oronts work with?

We work with all major AI agent frameworks and model providers including Mastra AI, LangChain, LangGraph, CrewAI, OpenAI, Anthropic, and open-source models. For orchestration, we use Mastra AI and LangGraph when workflows require complex multi-step reasoning with conditional branching, and CrewAI for collaborative multi-agent systems where specialized agents work together on tasks like research and content generation. On the model side, we select providers based on your requirements: OpenAI GPT models for general-purpose tasks with strong instruction following, Anthropic Claude for long-context analysis and nuanced reasoning, and open-source models like Llama or Mistral when data privacy requires on-premise deployment. Our AI development team selects the right stack for each LLM integration based on your specific requirements and constraints, including latency targets, cost budgets, data residency rules, and accuracy benchmarks. We also design systems to be model-agnostic where possible, so you can swap providers as the landscape evolves without rewriting application logic.

What is the typical timeline for an AI project with Oronts?

Our 90-day pilot program delivers a production-ready AI solution with defined success criteria. During those 90 days, we move through discovery, architecture design, implementation, and validation in structured two-week sprints. The first two weeks focus on understanding your data, defining success metrics, and designing the system architecture. Weeks three through ten cover core development, including model selection, pipeline construction, integration with your existing systems, and iterative testing against your defined benchmarks. The final weeks handle production hardening, monitoring setup, documentation, and knowledge transfer to your team. Full enterprise deployments typically take 3-6 months depending on scope, integration complexity, and compliance requirements. Factors that extend timelines include multiple system integrations, custom model fine-tuning, regulatory review processes, and multi-region deployment needs. We provide a detailed project timeline with milestones during the discovery phase so you have clear visibility into each delivery stage.

Enterprise AI Platform

AI That Actually Delivers

AI agents and LLM integrations that connect to your tools, automate business workflows, and drive measurable impact. Start with a 90-day pilot to production, with milestones you can hold us to.

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How Oronts AI Works

Oronts delivers custom enterprise AI systems. Our 'AI Platform' refers to a delivery and orchestration architecture, not a mandatory SaaS license.

You own the code, models, and infrastructure. We design, build, and operate with you. No lock-in.

Oronts is an AI development agency based in Munich, Germany. We build custom AI systems that integrate directly into existing enterprise workflows. Organizations do not need to adapt their processes to a rigid platform. Each engagement starts with a discovery phase. Our engineers map client data sources, toolchains, and business logic. Then we design an architecture tailored to specific operational requirements. The resulting systems combine LLM integration, retrieval-augmented generation (RAG systems), computer vision, and predictive analytics. We use modern AI agent frameworks including Mastra AI, LangChain, LangGraph, and CrewAI to build production-grade agentic AI solutions. Mastra AI powers our TypeScript-based agent workflows with built-in memory, tools, and RAG capabilities. These cohesive AI workflows run on the client's own infrastructure. Organizations retain full ownership of their models, training data, and deployment environments. Oronts specializes in AI automation and agentic AI. Autonomous AI agents handle multi-step business automation tasks like document processing, customer inquiry routing, quality inspection, and supply chain optimization. Human oversight is applied at critical decision points. Our AI consulting team in Munich serves clients across Germany and globally. Our 90-day pilot methodology structures each project into weekly deliverables. Measurable success criteria are agreed upon before work begins.

Across the systems we build

99.9%

Uptime SLA target

contractual target on managed workloads

AI agents in production

Mastra runtime on this site

GDPR

EU-first engineering

data protection by design

Published open-source packages

2 published open source

Quick Fit Check

Is Oronts AI Right for You?

Best For

Enterprises with complex workflows
Regulated industries needing compliance
Teams shipping AI to production
CTOs who need control and observability

Not For

Simple chatbot experiments
Prompt-only automation needs
No-budget proof-of-concepts
Teams without technical resources

Build custom AI when the answer lives in your own data

Buy a hosted AI tool when a generic chatbot or summarizer is enough and your data can leave your environment. Build a custom AI system when answers must come from your own documents, records, and rules, when the model needs to call your systems and take actions, and when wrong answers carry real cost. Production-grade AI for us means four things in every build: retrieval over your sources so responses are grounded and citable, tool-use so the model reads and writes your systems under controlled permissions, human approval gates on consequential actions, and a full audit trail. Your data stays in your cloud and provider boundaries are written into the contract.

Retrieval over your sources, so every answer is grounded and traceable to a document
Tool-use under scoped permissions, so the model acts inside your systems, not around them
Human approval gates on consequential steps, with low-confidence cases routed to a person
Full audit trail and your data kept inside your own cloud, not a third-party silo

RAG and multi-agent architecture

A bounded flow where retrieval stays permission-aware, agent tools stay scoped, and a human approves before anything ships. Every step writes to an audit log.

Approved sources

Permission-aware retrieval

Model / agent (bounded tools)

Human approval

Audit log

Guardrails and feedback across every step

Approved sources feed permission-aware retrieval. The model and its agent run on bounded tools, a human approves the result, and the audit log records the full chain. Guardrails and a feedback loop wrap every step.

From Idea to Production Agents

AI agents, RAG systems, AI workflows, memory and observability, engineered as a cohesive system.

Role Design

Planner, researcher, executor with clear responsibilities

Capabilities & toolsGuardrailsEscalation paths

Technical impact

Clear role boundaries & capabilities
Scoped tool permissions per role

Business outcomes

Fewer failure modes
Faster cycle time

handoff accuracytime-to-completion

Tooling

API calls, webhooks, search, DB and third-party integrations

OAuth & secretsRate limitsRetry/backoff

Technical impact

Retries with backoff
Circuit-breakers for flaky tools

Business outcomes

Higher success rate
Lower incident cost

tool success %error rate

Safety & Evals

Policy checks and automated evaluations per task

Prompt guardrailsUnit & regression evalsRed-team tests

Technical impact

Automated eval harness
Dataset regression checks

Business outcomes

Reliable releases
Reduced model drift risk

pass rateeval coverage

Human-in-the-loop

Inline approvals and hand-offs for critical actions

Review queuesEscalation to expertsAudit trails

Technical impact

Review queues & approvals
Audit trails for actions

Business outcomes

Risk control
Compliance alignment

time-to-approvalescalation rate

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AI Orchestration

Orchestrator Workflow

A clear, auditable path from user intent to reliable outcomes.

Best for

Intent & Plan

Parse goal and compose a plan with milestones

PlanChecksAssumptions

Retrieve & Ground

Pull relevant knowledge via RAG and policies

CitationsContextPolicies

Act & Tool

Execute tools, APIs, workflows with retries

ActionsResultsLogs

Review & Align

Self-check, evals, and human oversight when needed

ScoresNotesEscalations

Deliver & Learn

Return outputs and update memory for next time

ArtifactsMemoryFeedback

Consulting & Delivery Milestones

Discovery

1–2 weeks

Use cases & KPIs
Data & tool map
Risk & compliance

Architecture

1–2 weeks

Agent roles & tools
RAG & memory plan
Safety & observability

Pilot

3–6 weeks

Working agents
Evals & dashboards
ROI snapshot

Production

ongoing

SLA & runbooks
Alerts & ops
Iteration roadmap

Ready to map your orchestration & delivery?

Get a plan

See example

Core AI Capabilities

Our AI development platform combines LLM integration, agentic AI, and workflow automation to deliver intelligent solutions for every business need.

Natural Language Processing

Understand and generate human-like text with advanced language models

Sentiment Analysis

Text Generation

Translation

Summarization

Computer Vision

Analyze images and videos with advanced visual recognition

Object Detection

Face Recognition

OCR

Image Generation

Predictive Analytics

Forecast trends and outcomes with machine learning algorithms

Sales Forecasting

Risk Assessment

Demand Prediction

Anomaly Detection

AI Workflow Automation

Automate complex business workflows with AI-driven decision making

Business Process Automation

AI Workflow Orchestration

Resource Optimization

Quality Control

Natural Language Processing

Understand and generate human-like text with advanced language models

Multi-agent systems

Agentic AI Platform

Multi-agent orchestration with visibility, control, and scale. We design, build, and operate reliable agents across your stack and tools.

Capabilities at a glance

Visibility & Control

Fast Iteration

Durable Performance

Model Neutral

Visibility & Control

Step-level tracing, tool calls, retries, guardrails, and human-in-the-loop

Fast Iteration

Build → test → deploy loops with evals and production feedback

Durable Performance

Long-running workloads, queues, and recovery for enterprise SLAs

Model Neutral

Bring your LLMs, vector DBs, tools, and infra. no lock-in

Multi-Agent Orchestration

Coordinate specialized agents with shared memory and explicit hand-offs.

Role-based crews (planner, researcher, executor)

Tool & API integration at each step

Shared memory, RAG and long-term context

Safety constraints and escalation paths

Use cases

Customer supportSales co-pilotAnalyst assistant

KPIs

first-contact resolutionhandle timequality score

Framework Expertise

We meet you where you are and choose the right stack for the job.

CrewAI

Leading multi-agent orchestration for role-playing agents

Production-grade orchestration

LLM-agnostic

Production-ready patterns

Multi-agent

Orchestration

LangChain

Comprehensive agent engineering platform

Tracing & control

Rapid iteration

Durable infra

Model neutral

Agent engineering

Platform

LangGraph

Graph-based control for reliable multi-agent systems

Deterministic flows

Recovery paths

Human oversight

Graph control

Reliability

VoltAgent

TypeScript agent framework with great DX

Full control

Fast orchestration

RAG & tools

TypeScript

Mastra AI

TypeScript AI agent framework for workflows, RAG, and LLM integration

AI agents & workflows

RAG systems

Memory & tools

LLM integration

Business automation

TypeScript

AI Agents

Microsoft Agent Framework

Open-source engine for agentic AI apps

Composable

Observability

Evals

Open-source

Enterprise

Capabilities at a glance

Visibility & Control

Step-level tracing, tool calls, retries, guardrails, and human-in-the-loop

Fast Iteration

Build → test → deploy loops with evals and production feedback

Durable Performance

Long-running workloads, queues, and recovery for enterprise SLAs

Model Neutral

Bring your LLMs, vector DBs, tools, and infra. no lock-in

Multi-Agent Orchestration

Coordinate specialized agents with shared memory and explicit hand-offs.

Role-based crews (planner, researcher, executor)

Tool & API integration at each step

Shared memory, RAG and long-term context

Safety constraints and escalation paths

Use cases

Customer supportSales co-pilotAnalyst assistant

KPIs

first-contact resolutionhandle timequality score

Framework Expertise

We meet you where you are and choose the right stack for the job.

Orchestration

Coordinate and route work across specialized agents, with state and reliability.

CrewAI

Leading multi-agent orchestration for role-playing agents

Production-grade orchestrationLLM-agnosticProduction-ready patterns

Multi-agentOrchestration

LangGraph

Graph-based control for reliable multi-agent systems

Deterministic flowsRecovery pathsHuman oversight

Graph controlReliability

LangChain

Comprehensive agent engineering platform

Tracing & controlRapid iterationDurable infraModel neutral

Agent engineeringPlatform

Agent DX and TypeScript

TypeScript-native agent frameworks with strong developer experience.

VoltAgent

TypeScript agent framework with great DX

Full controlFast orchestrationRAG & tools

TypeScriptDX

Mastra AI

TypeScript AI agent framework for workflows, RAG, and LLM integration

AI agents & workflowsRAG systemsMemory & toolsLLM integrationBusiness automation

TypeScriptAI Agents

Enterprise platform

Composable, observable engines for enterprise agentic apps.

Microsoft Agent Framework

Open-source engine for agentic AI apps

ComposableObservabilityEvals

Open-sourceEnterprise

Custom AI Engineering

Custom AI Solutions

Built for Your Business

We design, build, and deploy AI systems tailored to your enterprise's unique needs

Custom LLM Integration

Language Model

Domain-tuned language models grounded in your own data and processes.

RAG

Grounding

Human review

Oversight

Multilingual

Languages

EU option

Hosting

Retrieval-augmented generation over your documents and knowledge base

Citations and guardrails on every answer

Fine-tuned on your domain terminology

Deploy in your cloud or EU-hosted infrastructure

Use Cases: Customer service, content generation, analytics

Computer Vision Systems

Computer Vision

Visual recognition trained on your products, sites, and workflows.

Custom

Training

Human review

Oversight

Multi-format

Formats

Your cloud

Deployment

Defect and anomaly detection trained on your images

Works with existing cameras and image formats

Edge or cloud inference to match your latency needs

Human review queue for low-confidence cases

Use Cases: Manufacturing QC, security, retail analytics

Predictive Analytics

Predictive Engine

Time-series forecasting and anomaly detection on your operational data.

Time-series + ML

Methods

Backtested

Validation

Drift alerts

Monitoring

Scheduled

Updates

Forecasts demand, load, and revenue from your history

Anomaly detection with explainable signals

Backtested against your past data before go-live

Drift monitoring with scheduled retraining

Use Cases: Demand forecasting, risk management, optimization

Workflow Automation

Intelligent orchestration and decisioning across your existing systems.

Audit-logged

Control

Human

Handover

API-first

Integrations

Retries + DLQ

Recovery

Orchestrates multi-step processes across your systems

Human handover on decisions that need sign-off

API-first integration with your existing stack

Audit log, retries, and dead-letter recovery

Use Cases: Business process automation, workflow optimization

Custom LLM Integration

Language Model

Domain-tuned language models grounded in your own data and processes.

RAG

Grounding

Human review

Oversight

Multilingual

Languages

EU option

Hosting

Retrieval-augmented generation over your documents and knowledge base

Citations and guardrails on every answer

Fine-tuned on your domain terminology

Deploy in your cloud or EU-hosted infrastructure

Use Cases: Customer service, content generation, analytics

Computer Vision Systems

Computer Vision

Visual recognition trained on your products, sites, and workflows.

Custom

Training

Human review

Oversight

Multi-format

Formats

Your cloud

Deployment

Defect and anomaly detection trained on your images

Works with existing cameras and image formats

Edge or cloud inference to match your latency needs

Human review queue for low-confidence cases

Use Cases: Manufacturing QC, security, retail analytics

Predictive Analytics

Predictive Engine

Time-series forecasting and anomaly detection on your operational data.

Time-series + ML

Methods

Backtested

Validation

Drift alerts

Monitoring

Scheduled

Updates

Forecasts demand, load, and revenue from your history

Anomaly detection with explainable signals

Backtested against your past data before go-live

Drift monitoring with scheduled retraining

Use Cases: Demand forecasting, risk management, optimization

Workflow Automation

Intelligent orchestration and decisioning across your existing systems.

Audit-logged

Control

Human

Handover

API-first

Integrations

Retries + DLQ

Recovery

Orchestrates multi-step processes across your systems

Human handover on decisions that need sign-off

API-first integration with your existing stack

Audit log, retries, and dead-letter recovery

Use Cases: Business process automation, workflow optimization

Full IP Ownership • Your Code, Your Models

Build Your Custom AI

Let’s discuss how custom AI solutions can transform your business with systems tailored to your needs.

Start Custom AI Project

View Our Methodology

Public engineering you can inspect

Running on this site

Live

The assistant on this site is an agentic, tool-using system we built and run in production, not a demo behind a login.

Vendure Data Hub

Open source

A Vendure commerce plugin we built and published, public on GitHub. Two of our eleven engineered bundles are public.

View on GitHub

Pimcore Asset Pilot

Open source

A Pimcore asset bundle we built and published, public on GitHub and inspectable end to end.

View on GitHub

Real use cases, described honestly

Customer support

Support tickets pile up. The system reads each ticket, classifies the intent and routes it or resolves routine cases, learning from agent feedback.

Routine tickets are resolved or routed automatically; agents focus on the cases that need judgement.

Procurement and supply chain

Stockouts and overstock tie up capital. The system pulls sales data, analyzes patterns, forecasts demand and proposes reorders for review.

Reorder signals surface earlier, so buyers act on data instead of gut feel.

Risk and fraud prevention

Suspicious transactions must be caught without blocking honest customers with false alarms. The system monitors transactions, scores them in real time and flags unusual patterns.

Suspicious patterns are flagged for review before approval, with a human making the final call.

Sales

Sales reps lose time to admin. The system tracks activity, suggests next actions, drafts follow-ups and updates the CRM.

Reps spend more time selling and less on admin, with the next best action surfaced in context.

Interactive Demo

Experience AI in Action

Try our AI capabilities with these interactive demos. No signup required.

When you work with us, you own the agents, code, models, and infrastructure.

AI Assistant

Hello! I'm your AI assistant. How can I help you today?

Illustrative demo with simulated responses. The production Oronts assistant is live in the corner of this page.

Hosted tool, glue code, or an engineered AI system

Three ways to put AI in your business, and what each one actually gives you. We build the third: a system you own, grounded in your data, governed end to end.

Scroll sideways to compare all three approaches.

	Hosted AI tool	API plus glue code	Engineered AI system
Data stays in your cloud
Retrieval over your own sources
Human approval gates on actions
Audit trail for every decision
Model-agnostic, swap providers freely
You own the code and the integration

1.5B

Parameters

Fast

Speed

Plus custom models trained on your data for maximum relevance

Ecosystem

Ecosystem & Tools

Technologies we work with every day, from ML frameworks to vector databases and APIs.

ML Frameworks

TensorFlowPyTorchNumPyGoogle ML Kit

Vector Databases

WeaviateMilvusQdrantChromaDeep LakeMindsDB

Audio Generation

Bark UITiny DiffusionAudio WebUIwhisper.cpp

LLM Training

Colossal-AIMegatron-LMDeepSpeed

Autonomous Agents

Mastra AICrewAIAgentGPTSuperAGIAutoGPTBabyAGIAdalaAgentlabsLocalGPTPinokioAgent4Rec

Stable Diffusion Stack

FooocusKrita AIInvokeAIVoltaMLSHARKFace FusionStable StudioSD Next

LLM Backends

llama.cppOllamaLocalAIKoboldCppgpt4allText Gen WebUIvLLMExLlama

AI APIs

OpenAIAnthropicMistralGroqGeminiCohereHuggingFaceOpenRouterPerplexityLiteLLMOctoAIAnyscaleStability AI

Built to clear your procurement and security review

The questions your legal, security, and data-protection teams ask, answered before they ask them.

Code ownership: You own the source code, the prompts, and the integration. No lock-in to a proprietary runtime you cannot leave.
Your cloud: The system runs in your cloud or on-premises environment. Data residency follows your tenancy, with EU hosting available.
Third-party model training: Configured so your data is not used to train third-party models, subject to each provider's terms and your chosen deployment mode.
AVV and GDPR: Auftragsverarbeitungsvertrag in place where required, with GDPR-aligned data handling, deletion paths, and documented processing.
Model and provider boundaries: Provider, region, and data-flow boundaries are defined in writing. Models are pluggable, so a provider change does not breach the contract.
Exit: Defined handover: code, infrastructure-as-code, documentation, and runbooks transfer to your team so you can operate or move the system without us.