Choose one process
Start with repeatable work that has a clear input, output, owner, and measurable time or cost.
AI agents and business process automation
AI agents that work
inside your business.
We help companies choose a process worth automating, prove the result in a controlled pilot, and connect the solution to the CRM, ERP, email, documents, databases, and internal systems they already use. Important decisions stay under your control.
- OpenAI
- Claude
- Gemini
- Grok Bot
- OpenClaw
- Copilot Studio
- n8n
- MCP
(01)
Where teams lose time
The strongest first candidates are frequent tasks with a clear input and outcome, accessible data, and manual steps that can be measured.
Email and requests
Read, classify, retrieve context, draft a response, and route each request to the right person.
GuideSales and CRM
Qualify leads, enrich records, summarise conversations, create tasks, and prepare follow-up for review.
GuideDocuments and finance
Extract invoice and order data, check business rules, reconcile records, and prepare entries for review.
GuideInternal knowledge
Answer employees’ questions using approved policies, procedures, and documents, with links back to the source.
GuideSupport and appointments
Triage requests, check availability, schedule appointments, and escalate complex cases to a person.
GuideReporting and data
Collect information across systems, check discrepancies, and produce recurring summaries and alerts.
Automation(02)
From assessment to production
We do not sell an “agent for everything.” Together we choose one process, prove the result in a bounded pilot, and expand only what works reliably.
- 01 Process assessment Map one real process, starting measures, data, exceptions, risks, and a pilot plan before choosing the technology.
- 02 Measured pilot Automate a bounded part of the process, test real cases, and compare cycle time, errors, and manual effort with the starting point.
- 03 Production rollout Connect the proven solution to systems and data, then set permissions, approvals, logs, monitoring, and a safe expansion plan.
If the team first needs shared rules and practical experience, we also provide AI training built around a real business process.
(03)
How we deploy automation safely
Connect the right systems
Map data sources and actions, then choose the model, agent product, or workflow platform that fits your environment.
Set the boundaries
Use least-privilege access, human approvals, action logs, test cases, and a safe exit when the agent is uncertain.
Pilot and measure
Measure cycle time, errors, and manual effort. Expand to the next process only after the pilot works reliably.
The same sequence, spread across the first month, is set out in the 30-day plan for introducing AI.
(04)
When automation needs its own application
Digitalization and application development support the same goal. When off-the-shelf software does not fit the real process, we build a clear interface connected to existing systems and ready to grow.
From a manual process to a digital product your team and customers genuinely want to use.
- 01
Process digitalization
We turn paper, spreadsheets, email, and disconnected steps into a clear digital workflow with data in one place.
- 02
Web and mobile applications
We build customer portals, internal tools, MVP products, and custom applications for web, iOS, and Android.
- 03
Integrations and data
We connect the application to your CRM, ERP, databases, external services, and APIs so information flows without duplicate entry.
- 04
From idea to production
Together we define the problem, shape the user experience, build the first version, and iterate from real user feedback.
(05)
Technology follows the process
A model, an AI agent, and an automation platform do different jobs. Only after understanding the process do we choose the simplest mix for your systems, data, permissions, complexity, and required oversight.
Model APIs
Depending on the task, we evaluate the OpenAI API, Claude API (Anthropic), Gemini API (Google), and xAI API.
AI assistants and agent tools
For assistants and agent products, we evaluate ChatGPT Work, Grok, Grok Bot, and the open-source OpenClaw, which runs on your own infrastructure or devices.
Frameworks and SDKs
For custom agents, we evaluate the OpenAI Agents SDK, Claude Agent SDK, and Google’s Agent Development Kit (ADK).
Workflow platforms
For orchestration, we evaluate n8n, Microsoft Copilot Studio, Zapier Agents, Make AI Agents, and the UiPath Platform for each project.
System connections
Existing connectors may be used when they fit. For authorised internal tools, we can design connections through REST APIs, webhooks, function calling, and the Model Context Protocol (MCP), subject to platform support and permissions.
Final selection depends on a technical assessment, licensing, permissions, data governance, and platform constraints. Product names identify potential technologies and integration targets; they do not imply partnership, certification, vendor endorsement, or guaranteed compatibility. How that decision is made is covered in the n8n, Copilot Studio, Make, and Zapier comparison and the guide to choosing a model and platform.
The best bot is not the one with the newest model. It understands your process, has only the permissions it needs, asks for approval at the right time, and reliably completes work you can measure.
(06)
AI agent questions
What is the difference between a chatbot and an AI agent?
A chatbot mainly answers questions. An AI agent can use tools, retrieve data, and perform pre-approved actions in business systems, with rules, logs, and human approval when needed.
Can an AI agent connect to our CRM, ERP, or database?
It can when the system provides a supported connector, API, webhook, or MCP server and the required permissions are available. We assess data access, security boundaries, and monitoring before connecting it.
Which AI agent platform is best for our company?
The choice depends on the process, systems, licences, data, and level of control. n8n is an AI workflow automation platform, while OpenClaw is an open-source AI assistant that runs on your own infrastructure or devices and requires stronger boundaries and operational oversight. Microsoft Copilot Studio often fits Microsoft 365 environments, while Zapier Agents or Make AI Agents may fit common SaaS integrations.
How do we deploy an AI agent safely?
We start with one measurable process and least-privilege access. High-impact actions require human approval, important actions are logged, and the pilot is tested and monitored before expansion.
What should we automate first?
A good first candidate is frequent, repetitive work that consumes measurable time, has accessible data, and carries manageable risk. Email, documents, CRM updates, and recurring reports are often better starting points than one broad “agent for everything.”
What does AI automation cost, and how do we measure return?
Cost depends on the number of systems, API availability, process variability, risk, and volume. We scope the pilot after mapping the steps, and measure return through cycle time, manual effort, errors, and response time. Licenses and model usage are estimated separately. Use the AI agent cost and ROI guide with your own inputs.
Where is data processed, and can the solution run in the EU or be self-hosted?
Processing location depends on the selected provider and architecture. We assess EU regions or self-hosting, data retention, access permissions, contractual obligations, and applicable compliance requirements for the specific solution.