AI Automation & Agentic Systems

Repetitive work in your company gets handed to an agent. We build it, connect it to the systems you already run, and make sure it stays trustworthy once it is live.

A run with human review

01document
Invoice arrives in the shared folder
0.0s
02extract
Agent reads the fields and checks them against the order
6.0s
03review
A person sees the proposal and approves or corrects it
—
04approved
Decision recorded as evaluation data
+2s
05write: erp
Approved record written into the target system
45s

Manual

2 h 10 min

Agent + review

45 s

Illustrative run

On this page

Agentic Systems AI Workflows & Automation Integration & Operations

Agentic Systems

We design, build, and run AI agents that work inside your product and your operations — including the applications they live in. From agents that handle natural language and documents to retrieval over your own data. We take care of architecture, orchestration, security, and production monitoring.

When it makes sense

Internal knowledge

Querying documentation, databases, tickets, or internal know-how through retrieval pipelines, with the source attached to every answer.

A copilot inside your product

An assistant in the application itself, helping users work with data, configuration, or content in plain language.

Agentic applications, end to end

A new application where agents are part of the architecture from day one — interface, server, and agent layer delivered together.

Agents with real permissions

Cases where the agent does not only answer but performs actions in a system that matters.

What we deliver

Agent systems

We design and implement AI agents — models equipped with tools and APIs, with structured inputs and outputs. We connect them to your systems, teach them your domain, and put them into a pipeline or a chat interface.

Tooling and orchestration

A layer between your application and the agent built on MCP servers, agent SDKs, or CLI tools. It gives agents controlled, auditable access to your systems and data.

RAG over your data

Complete retrieval pipelines: data preparation, retrieval, answer generation, and quality evaluation — so answers cite real, current information.

Agentic applications: interface and server

When the agent needs somewhere to live, we build it: the web UI your team works in, the server the agents run and communicate over, and the agent layer itself. One team delivers all three, so nothing gets stitched together afterwards.

Identity, permissions, and audit trail

The agent acts under a specific identity and only within its rights. Every step, tool call, and change stays traceable. This is what decides whether an agent is allowed into a live system.

How we keep it trustworthy

Permissions

The agent acts under a specific identity and only within its rights. Never “on behalf of the company”.

A person in the loop

We start with every output being approved. We loosen that only as measured accuracy allows.

Evaluation

Reviewer decisions are collected as test data. Accuracy is a number, not a feeling.

Monitoring

Every run, every tool call, and every error can be traced back.

Reversibility

When something goes wrong, you know which run it was, what it did, and how to undo it.

FAQ

What if the AI makes things up?

The agent answers over your data and links to the source. Before anything goes live, we measure accuracy on your real cases, and a person stays in the loop until the numbers are convincing.

Our data cannot leave the company.

We decide together where the model runs and what it can reach. The agent acts under a specific identity, limited to that identity's rights. Where it makes sense, the whole deployment runs inside your infrastructure.

We tried a chatbot and it did not help.

A chatbot answers. An agent finishes the work: it opens your system, makes the change, and writes down the result. The difference is not the model — it is the integration and what the agent is allowed to do.

Can you build the application around the agent too?

Yes. We build the web interface your team works in and the server the agents run on, alongside the agent layer itself.

Do you train custom models?

We can, but most companies do not need it. If a hosted model plus good integration gets you there, we will say so and save you months.

Who runs it after you are gone?

Monitoring, documentation, and access are yours from the start. You see the runs, not us. Handover is part of the delivery, not an add-on.

Tech stack

Agents

Agent SDKs
MCP
RAG
Evals

Backend

Python
FastAPI
Node.js
Postgres
Vector DBs

Operations

Docker
CI/CD
Monitoring
Access control

Thirty minutes, free, no strings.

Agentic Systems

Bring one process from Agentic Systems and we will tell you whether an agent fits it — or whether something cheaper does.

Pick a time Contact

AI Workflows & Automation

We take repetitive, time-consuming work off your team. We design and run automations that connect systems, orchestrate multi-step processes, and bring in agents where fixed rules are not enough — with a person approving the output until the numbers say otherwise.

When it makes sense

Inbox and document workflows

Daily email triage and summaries, suggested replies, or splitting PDFs and notes into actionable tasks in your tools.

Process automation across teams

Internal processes that cross several systems, from simple flows to orchestrations with approvals and error paths.

Approvals and deadlines

Routing work to the right person, chasing what has not come back, and keeping operational deadlines from slipping.

Keeping records current

Agents update CRM and ERP records, spot missing data, and prepare the follow-ups.

What we deliver

Workflow orchestration

Design and implementation of end-to-end workflows, including agent steps, dependencies, approval gates, state handling, scheduling, and error scenarios.

A review screen for people

A person sees what the agent proposed and approves, corrects, or rejects it. Those decisions are collected as evaluation data, so the agent's accuracy is measured rather than assumed.

Write-back into your system

The approved output is written where it belongs. Automation that never writes the result back is not automation — it is one more tool to click through.

AI workflow assistants

Practical assistants for operations: inbox copilots, document-to-task pipelines, and workflow control through the chat tools your team already uses.

Monitoring and reliability

Tracking runs, errors, throughput, and operational stability, with retries you can trigger and audit.

How we keep it trustworthy

Permissions

The agent acts under a specific identity and only within its rights. Never “on behalf of the company”.

A person in the loop

We start with every output being approved. We loosen that only as measured accuracy allows.

Evaluation

Reviewer decisions are collected as test data. Accuracy is a number, not a feeling.

Monitoring

Every run, every tool call, and every error can be traced back.

Reversibility

When something goes wrong, you know which run it was, what it did, and how to undo it.

FAQ

Which processes are worth automating?

Ones that repeat, take time, follow reasonably clear rules, and move data between several systems. If a process runs three times a year, we will tell you to leave it alone.

Can it connect to the systems we already have?

Yes. We design automations around your current tools and APIs, including older systems that only offer limited access.

What if the agent gets something wrong?

Until accuracy is proven, every output passes through a person. After that, the agent runs on its own and a person handles only edge cases and low-confidence results.

Can we monitor automation in production?

Yes. You see runs, errors, and throughput, and you can retry any run. The record is yours.

Do you only work with n8n?

No. We use n8n where it fits, and build custom orchestration when reliability, scale, or deeper integration calls for it.

How much of our time will this take?

Two to three hours of interviews for the audit. The build and the operation are on us.

Tech stack

Orchestration

n8n
Custom orchestrators
Queues
Schedulers

Integration

REST APIs
Webhooks
Event-driven
Slack / Teams

Operations

Monitoring
Retries
Audit logs

Thirty minutes, free, no strings.

AI Workflows & Automation

Bring one process from AI Workflows & Automation and we will tell you whether an agent fits it — or whether something cheaper does.

Pick a time Contact

Integration & Operations

We plug agents into the systems you already run and keep them running afterwards. Most of the work on an agentic system is not the model — it is the integration, the permissions, and the operations.

When it makes sense

Connecting to CRM, ERP, and internal APIs

Bringing agents and workflows into the systems your company runs on, including in-house tools.

Bringing data together

Consolidating information spread across several systems so an agent has something reliable to work from.

Sensitive data and access control

Cases where an agent has to reach data that not everyone is allowed to see.

Taking over an existing solution

Stabilising, documenting, and operating an AI system somebody else built.

What we deliver

Connectors to your systems

Integration through APIs, webhooks, or event-driven architecture, including retries and error handling for systems that are not always available.

MCP servers and tool layers

A controlled interface between agents and your systems, so every action an agent can take is explicit and reviewable.

Data pipelines and preparation

Getting your data into a shape an agent can actually use: cleaning, structuring, indexing, and keeping it current.

Monitoring, evals, and alerting

Runs, errors, latency, and accuracy tracked in one place, with alerts when behaviour drifts.

Handover and documentation

Access, runbooks, and documentation on your side, so you can operate the system without us.

How we keep it trustworthy

Permissions

The agent acts under a specific identity and only within its rights. Never “on behalf of the company”.

A person in the loop

We start with every output being approved. We loosen that only as measured accuracy allows.

Evaluation

Reviewer decisions are collected as test data. Accuracy is a number, not a feeling.

Monitoring

Every run, every tool call, and every error can be traced back.

Reversibility

When something goes wrong, you know which run it was, what it did, and how to undo it.

FAQ

Our systems are old. Will this work?

Usually yes. If a system offers an API, we integrate through it. If it does not, we look for another route — and if there is none worth the cost, we will say that too.

How do you handle access to sensitive data?

The agent has its own identity with the narrowest rights that still let it do the job, and every access is logged.

Can you take over a system somebody else built?

Yes. We start by adding monitoring and evaluation, so we can see what it actually does before changing anything.

What does running it cost?

It depends on volume and on which models are involved. We estimate build cost and running cost together during the audit, before anything is built.

What happens when a model provider changes something?

The tool and integration layer is ours, not the provider's. Swapping a model is a configuration change, not a rebuild.

Do you hand the system over to our team?

Yes. Documentation, access, and runbooks are part of the delivery.

Tech stack

Integration

MCP
REST APIs
Webhooks
Message queues

Data

Postgres
Vector DBs
ETL pipelines

Operations

Docker
CI/CD
Observability
Alerting

Thirty minutes, free, no strings.

Integration & Operations

Bring one process from Integration & Operations and we will tell you whether an agent fits it — or whether something cheaper does.

Pick a time Contact

Two systems that already run

An agentic system operating a data platform under user permissions, and workflow applications where a person approves what the agent proposes before it is written back.

Read what was built

How we start

The first step is a thirty-minute call. Not a project.

01
Intro call
Thirty minutes, free. Bring one process and we will tell you whether an agent fits it.
02
Automation audit
Five working days. A map of your processes, three ranked candidates, and a technical proposal.
03
Pilot
One process, a success criterion agreed up front, a person approving every output.
04
Production
Deployment with monitoring, access control, and documentation on your side.
05
Rollout
More processes on the same foundation, cheaper than the first one.

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