AI Solutions — from fast n8n agents to enterprise-grade orchestration
We implement AI as a managed system: with control, auditing, security, and scalability – from quick solutions to enterprise-level platforms.
Quick Launch: PoC in weeks, first effects immediately
Full transparency: tracing of inputs/outputs, decisions and actions
Without vendor lock-in: open-source stack + clear architecture
Choose the right level for your AI initiative
The three proposals cover different requirements for implementation speed, process complexity and level of control.
Custom AI Agents Platform
Custom AI Agents Platform
AI-driven agents with orchestration, observability, and end-to-end auditability for processes where the cost of error is high
This is not a “bot”, but an engineering platform: standardized logic, access control, auditing, reproducibility and the ability to improve behavior without chaos.
What you get
Standardized agent workflows (LangGraph)
Orchestration and Task Management (Prefect)
Connecting to corporate systems via MCP
Agent versioning and reproducibility
End-to-end tracing and observability (LangSmith)
Full audit: inputs, decisions, actions (Operaton)
Access management and security policies
Metrics, dashboards, data-driven improvement
Audit timeline
Step 1
Request received
Step 2
Context fetched
Step 3
Decision made
Step 4
Action executed
Example: FM AI Platform with Audit & MCP
Best fit
Finance, risk analysis, compliance
Long processes (hours/days), waits, external dependencies
Many systems and complex integrations
Requirements for transparency and change control
Build an enterprise-grade AI platform
Get expert guidance on architecture and implementation
n8n AI Agent
A fast AI assistant for RAG, support, and simple solutions – minimal infrastructure, maximum startup speed.
Typical capabilities
- RAG by knowledge base (Notion/Confluence/Docs/DB)
- Request classification and routing (support/sales/ops)
- Easy integrations: CRM, email, Slack/Teams, forms, webhooks
- FAQ / support assistant
- Generating answers, brief summaries, and checklists
Example: lightweight ordering assistant
A user writes on Telegram: “I want something spicy, but no meat, delivery in 30 minutes.”
The agent retrieves menu information from the knowledge base, clarifies the order details, and transmits the data to the ordering system.
Launch: 1-2 weeks
Infrastructure: minimal
Best fit
Quickly test a hypothesis (PoC)
Need an inner helper “yesterday”
There are no requirements for complex orchestration and in-depth auditing
Limited budget
Launch an n8n AI agent fast
Get a proof-of-concept plan tailored to your needs
AI Automation & Orchestration
Business process automation with AI: from simple workflows to BPMN orchestration with auditing.
Layer A n8n workflows
Simple automations
Fast integrations
Event-driven flows
Layer B: BPMN / Operaton
Complex orchestration
Full audit trail
Compliance ready
Same EAAF principles — different orchestration depth
n8n — Simple & Fast Automations
Ideal for simple processes and quick integrations. Visual editor, extensive connector library, minimal learning curve.
Use cases:
- Simple sequential processes
- Integration between systems
- Automation of routine tasks
- Data processing and notifications
Start
Process
Complete
BPMN / Operaton — Complex Processes
Enterprise-grade orchestration with full auditing and versioning. Standard BPMN 2.0 notation, state management, and rollback capabilities.
Use cases:
- Complex business processes with branching
- Processes requiring compliance and audit
- Long-running processes with human-machine interaction
- Processes with parallel execution of tasks
Start
Gateway
Audit & Complete
Orchestrate business processes with full audit
Map your processes and choose the right orchestration approach
Delivery approach
01
Discovery & process mapping
We identify automation points and risks
02
PoC / Pilot
We quickly check the value and collect metrics
03
Productionization
security, RBAC, observability, testing
04
Scale & optimize
quality improvement, cost, version control
Compare solutions
| Feature | n8n AI Agent | AI Automation | Custom Platform |
|---|---|---|---|
| Launch speed | 1-2 weeks | 2-4 weeks | 4-8 weeks |
| Complexity of logic | Simple | Medium-High | Very high |
| Audit & Compliance |  |  | |
| Observability | Basic | Average | Complete (LangSmith) |
| Orchestration | Built into the n8n | n8n or BPMN | Prefect |
| Versioning | | | |
| Scalability | Limited | Average | High |
| Team Requirements | Minimum | Average | DevOps + ML engineers |
| Cost of implementation | $ | $$ | $$$ |
FAQ
How does your approach differ from ready-made AI platforms?
Unlike off-the-shelf AI tools, we don’t offer a generic solution that you have to adapt your processes to. We design AI around your actual workflows, data, and business goals — and integrate it into your existing systems. The result is automation that fits your operations, not the other way around.
How quickly can you launch your first PoC?
In most cases, the first Proof of Concept can be launched within 2–6 weeks. We start with a focused, high-impact use case, quickly validate value, and then move toward scaling what works.
What are the quality and safety guarantees?
We implement human-in-the-loop controls, validation rules, and full process transparency. Every AI workflow is monitored, logged, and measurable. This ensures reliable performance, controlled risks, and compliance with your internal policies.
Is it possible to start with a simple solution and then scale it up?
Absolutely. We recommend starting with a small, well-defined automation that delivers quick value. Once proven, the same architecture can be expanded into more advanced AI agents, cross-department workflows, and enterprise-level orchestration.
What if we don’t have our own team of ML engineers?
That’s completely fine — most of our clients don’t. We provide the full stack: strategy, architecture, development, and ongoing support. Your team stays focused on business expertise while we handle the AI and automation side.
How is the impact of AI implementation measured?
We define success metrics at the start of every project — typically time saved, cost reduction, error rate decrease, or revenue impact. Dashboards and reports make performance visible, so you can clearly see ROI and operational improvements.
Ready to implement AI with control
and measurable ROI?
Describe your process or use case, and we’ll suggest a suitable implementation level and PoC plan.
Control
Audit
Orchestration