AUTOMATION · AI AGENTS
AI agents for your workflows
We design and deploy AI agents that handle defined, recurring tasks across the tools your team already uses. Each agent connects to your approved systems and works within agreed permissions, with human review where the workflow requires it.
What we deliver
A working AI agent, or a small team of agents, built around a defined workflow. Each agent connects to approved tools and data sources, uses relevant context, and carries out agreed tasks within clear permissions and review points.
- Custom agents designed around your recurring tasks
- Integration with your agreed CRM, advertising platforms, internal tools, and data sources, confirmed during technical assessment
- Claude as the default, with Copilot, OpenAI, or locally hosted models considered where suitable
- MCP connections for retrieving information and using approved tools, where appropriate for the workflow
- Defined permissions, human approval steps, and exception handling
- Logs of agent actions, outputs, and approvals to support review
- Support for Danish, English, and other agreed languages
- Documentation covering configuration, operation, and maintenance
- 30 days of refinement support after launch
How we work
We begin by understanding the task: how it is carried out today, who is responsible, and what information it requires. Together, we agree what the agent can handle, where human review fits, and how success will be assessed. We then select suitable models and tools, build the connections, and test the workflow with your team before launch.
Outcomes
Less time spent gathering information and carrying out routine steps, with clearer handovers when a task requires human judgement. Your team can review agent activity and use the information gathered to support decisions.
- Reduced manual effort on agreed, recurring tasks
- Relevant information brought together for review and decisions
- Clear handovers for approvals, exceptions, and unresolved tasks
- Traceable records of agent actions and workflow outcomes
- A documented foundation for extending automation as requirements develop
- Support for teams working across agreed languages
WHERE AI AGENTS CAN HELP
Where AI agents can help
Recurring tasks, information spread across systems, and manual follow-up after decisions are three common starting points for exploring how AI agents could support your team.
Reducing Repetitive Work
Your team spends time gathering updates, preparing summaries, routing requests, and following up. We build agents that handle agreed routine steps and bring exceptions or questions to your team for review.
Connecting Agents to Relevant Context
An agent can only work effectively with the information available to it. We connect it to approved records, documents, and data sources so it can use relevant context when preparing responses or carrying out tasks.
Turning Decisions into Actions
Once a decision is made, the next step may still depend on someone updating records, transferring details, or assigning work. We enable agents to carry out these actions within agreed permissions, with approval steps where required and logs to support review.
Ready to put an AI agent to work?
Tell us which tasks take up your team’s time and the tools involved. In a free 30-minute conversation, we can explore where an AI agent could help and agree a practical next step.
OUR APPROACH
How we build your agent
The schedule below illustrates a five-week engagement. Actual timing depends on the agreed scope, system access, and testing requirements; more complex projects may take longer.
Map
Week 1
We map the tasks, tools, data sources, and responsibilities within your workflow. Together, we agree the scope, access requirements, human review points, and success criteria.
Design
Weeks 1–2
We select suitable models and design the agent’s instructions, tool connections, permissions, and logging. Before development begins, your team reviews how the agent will carry out tasks, request approval, and handle exceptions.
Build
Weeks 2–3
We build the agent and connect it to your approved systems, using MCP where appropriate. We configure access controls, approval steps, and action logging, testing each integration as the work progresses.
Test
Weeks 3–4
We test the complete workflow with your team using representative tasks and inputs. Together, we check output quality, permissions, human handovers, and how the agent responds to missing information or tool failures.
Deploy
Weeks 4–5
We launch the agent with monitoring, action logging, and an agreed process for pausing the agent or rolling back changes. Your team receives documentation and a walkthrough, followed by 30 days of refinement support.
WHAT YOUR AGENTS CAN DO
Triggers, actions, and integrations
A workflow begins with an event, a schedule, or a request. The agent uses relevant information and approved tools to carry out agreed actions, with human approval where required.
- Incoming email or message
- New or updated CRM record
- Scheduled task (daily, weekly)
- Question or request in chat
- File upload (CSV, PDF, image)
- Webhook from a connected system
- Summarise and classify information
- Draft responses and send once authorised
- Update records or route requests
- Retrieve information across systems
- Start the next workflow step
- Log actions, outputs, and approvals
- Email (Gmail, Outlook, IMAP)
- CRMs (HubSpot, Pipedrive, Salesforce)
- Messaging (Slack, Teams, Discord)
- Databases (PostgreSQL, MySQL, MongoDB)
- Vector stores (Pinecone, Weaviate, Chroma)
- Custom APIs and internal tools
Have a task or integration not listed here? Tell us about your tools and workflow. Together, we can explore what is possible.
MULTILINGUAL SUPPORT
Agents that work in your team’s language
We configure and test agents for the languages your workflow requires, including Danish, English, and other agreed languages. Responses reflect the audience, task, and terminology your team uses.
Danish in Daily Use
For Danish-speaking teams, we test outputs for clarity, tone, and relevant terminology. Your team helps refine the wording so it fits everyday communication.
Support Across Languages
Agents can support distributed teams and customer communication in English, German, French, and other agreed languages. We assess language quality for the intended tasks before launch.
Mixed-Language Workflows
When a conversation changes language, the agent responds according to the workflow’s language settings. For example, a workflow can be configured so that customer messages in Swedish receive replies in Swedish, while internal notes remain in Danish.
GROUNDED IN EXPERIENCE
Data and security expertise, applied to AI workflows
- More than 25 years of IT experience held by Alpha’s lead consultant
- Data protection built into workflow and agent design
- Expert-led delivery with one lead contact from scoping to handover
Alpha combines data architecture, governance, and cybersecurity expertise with practical agent development. You work directly with the consultants building your agent. From the start, we define how it accesses and handles data, which actions it can take, and where approval and logging support oversight.
QUESTIONS WE HEAR OFTEN
What to expect from your engagement
How much does an AI agent cost?
Pricing depends on the workflow, the number of agents and integrations, and the permissions and review steps involved. After scoping, we provide a fixed quote for the agreed work. We also identify any ongoing model, platform, or hosting costs so you can assess the full running cost.
How long does delivery take?
A typical engagement takes 3 to 5 weeks from kick-off to deployment. Timing depends on the scope, access to your systems, and testing with your team. We agree the delivery schedule before work begins.
Which AI models and platforms do you use?
Claude is our default. We also consider Microsoft Copilot, OpenAI models, or locally hosted models where suitable. Together, we select an approach based on your workflow, existing tools, data handling requirements, budget, and hosting preferences.
How do you use MCP?
MCP, or Model Context Protocol, provides a standard way for AI applications to connect to tools and data sources. We use it where appropriate to give your agent access to approved information and actions. Each connection still requires suitable configuration, permissions, and testing.
Will the agent work with our existing tools?
We assess your tools and available interfaces during scoping. Many platforms support connections through APIs, webhooks, or MCP servers. We confirm which information and actions are accessible, check any restrictions, and identify additional integration work before agreeing the scope.
How do you approach data security and GDPR?
We begin by identifying what data the agent requires, where that data is processed, and who can access it. The design addresses permissions, secure connections, retention, action logging, and human review. Where personal data is involved, we work with your team to assess provider arrangements and relevant GDPR requirements for the intended use.
Can our team adjust the agent later?
Yes, where the platform, architecture, and agreed permissions support it. We provide documentation and guidance explaining which instructions, settings, and routine configurations your team can change and how to test them. Changes to permissions, integrations, or workflow behaviour can be reviewed with Alpha or your technical team.
What happens after the 30-day refinement period?
Your team can continue operating the agent using the documentation and handover guidance. Ongoing support, additional integrations, or further agents can be covered through a separate support agreement or follow-up project. Ownership, licensing, and any continuing third-party costs are set out in the project agreement.
TALK TO ALPHA
Find the right starting point for your agent
Tell us which recurring tasks take up your team’s time and which tools you use. Together, we can explore whether an AI agent could help and what approach would fit your priorities and resources.