AI Workflow & Agent Development Services

A chatbot primarily responds to user input in a conversational way. An AI agent, on the other hand, can:

• Make decisions

• Execute actions

• Call external APIs and tools

• Maintain state and memory

• Operate autonomously without constant user input

  AI agents are designed for real business processes, not just conversations.

AI workflow automation refers to using AI to replace or enhance manual business processes, such as:

• Data entry and enrichment

• Document processing

• Customer support handling

• Internal reporting and analysis

Unlike traditional automation, AI workflows can handle unstructured data and make context-aware decisions.

AI Agents for business automations can serve multiple purposes:

• Internal process automation

• Customer support workflows

• Data analysis and reporting

• CRM and CMS automation

• Lead qualification and enrichment

• AI-powered internal tools

• Content operations and knowledge retrieval (RAG systems)

The best use cases are processes where people currently spend time gathering information, making routine decisions, or moving work between systems. In those cases, custom AI agents can reduce manual effort while keeping humans in control of exceptions and approvals.

Traditional automation relies on fixed rules and predefined logic.

AI workflows can:

• Interpret natural language

• Handle incomplete or messy data

• Adapt to different inputs

• Make probabilistic decisions

This makes them far more flexible for real-world business scenarios.

Yes. We build AI agents using OpenAI models, Anthropic Claude, and open-source LLMs, depending on your requirements around cost, performance, data privacy, and hosting. We help you choose the right model and architecture rather than locking you into a single vendor.

Yes. A big part of our work is AI agent integration services for existing web applications, internal tools, and backend workflows. We can connect AI agents to your current product, APIs, databases, auth systems, and third-party platforms without forcing a rebuild.

This often includes embedding agents into SaaS platforms, admin panels, customer support flows, or operations tooling. We also build AI workflow agents that can trigger actions, retrieve context, and coordinate multi-step processes inside your existing stack.

Common AI workflow examples include:

• Automatically classifying and routing support tickets

• Extracting data from PDFs and invoices

• Generating and reviewing content

• Enriching CRM data with external sources

• Summarizing internal knowledge and documents

• Processing cancellations, refunds, or requests

These workflows often span multiple systems.

AI agent development is industry-agnostic but particularly effective for:

• SaaS and B2B platforms

• E-commerce and marketplaces

• Media and publishing

• Professional services

• Fintech and legal tech

• Operations-heavy businesses

Anywhere repetitive decision-making or data-heavy workflows exist, AI agents add value.

No-code tools are great for simple workflows. Custom AI agents go further by:

• Handling complex logic and branching

• Reasoning over unstructured data

• Maintaining long-term memory

• Operating securely inside your infrastructure

• Scaling with your product

AI agent development is ideal when off-the-shelf automation tools hit their limits.

Yes, when built correctly. We design AI agents with:

• Secure API handling

• Controlled data access

• Explicit permission boundaries

• GDPR-aware data flows

• Optional EU-based hosting

Compliance and security are architectural decisions — not afterthoughts.

Yes. AI agents can securely access private data via:

• Retrieval-Augmented Generation (RAG)

• Vector databases

• Role-based access control

• Scoped API permissions

Your data is never used to train public models unless explicitly configured.

AI workflows can be built using:

• LLM APIs (OpenAI, Claude, open-source models)

• Workflow engines (e.g. n8n, custom orchestration)

• Backend services (Node.js, serverless functions)

• Vector databases for retrieval (RAG systems)

• API integrations with third-party systems

We typically combine off-the-shelf tools with custom code for flexibility.

A simple AI agent prototype can be built in 1 week.

Simple use cases can move fast, but most teams that want to build custom AI agents in production should expect a phased rollout. A production-ready setup often takes 2-6 weeks, depending on the number of integrations, workflow complexity, guardrails, and testing requirements.

For custom AI agent development, we usually start with one high-value workflow, ship it, measure how it performs, and then expand the agent’s scope over time. That reduces risk and gets useful automation live sooner.

Yes — and they should be. AI agents benefit from:

• Ongoing prompt optimization

• Model upgrades

• Monitoring and logging

• Performance tuning

• New integrations as your business evolves

We treat AI agents as long-term software systems, not one-off experiments.

No-code tools are suitable for simple use cases. Custom AI workflows are better when:

• Logic becomes complex

• You need reliability and error handling

• Security and compliance matter

• Workflows are core to your product

• Performance and scalability are critical

That’s where engineering becomes necessary.

AI agents are designed to augment teams, not replace them. They handle repetitive, time-consuming tasks so humans can focus on higher-value work such as strategy, creativity, and decision-making.

Our custom AI agent developers usually work with TypeScript and JavaScript-based product stacks, alongside the orchestration, retrieval, observability, and infrastructure tools needed for reliable AI systems. We build with the model layer that best fits the problem, including OpenAI, Anthropic, and strong open-source options when appropriate.

If you are looking for an LLM agent development company, the important thing is not loyalty to one model vendor. It is the ability to design the full system around your workflows, integrations, data boundaries, evaluation needs, and long-term maintainability.

RAG (Retrieval-Augmented Generation) is a technique where AI workflows:

1. Retrieve relevant data from a database or knowledge base

2. Provide that data to an LLM

3. Generate accurate, context-aware outputs

This allows AI workflows to work with private and up-to-date information.

Costs depend on:

• Agent complexity

• Number of integrations

• Hosting and model usage

• Security and compliance needs

Most projects start with a discovery phase followed by an MVP and iterative rollout. We provide transparent estimates based on real scope — not vague AI promises.

The best starting point is identifying one concrete workflow or problem that:

• Is repetitive

• Uses structured or semi-structured data

• Requires decision-making or reasoning

From there, we define the agent’s responsibilities, integrations, and success metrics.

The best starting point is identifying one concrete workflow or problem that:

• Is repetitive

• Uses structured or semi-structured data

• Requires decision-making or reasoning

From there, we define the agent’s responsibilities, integrations, and success metrics.

Yes, we sign an NDA (Non-Disclosure Agreement) always when a client wants it. We can do it at the very beginning before we discuss your project's details, or at another stage of the process - it's up to you.

Yes, you are the owner of Intellectual Property rights at all times.

We are fully remote. So while we were founded and are still based in Berlin, most developers will be remote from a central European location.

You work with us on a Time & Materials basis. The total cost depends on the actual time the team spends on the development. You are in charge of the project’s scope and set priorities for the development team.

Time & Materials allows flexibility for you to set the direction of development depending on the users’ feedback, market situation, or opportunities that arise during the development.

For more about how we create estimates read how to estimate software projects .

We adjust the team depending on your needs. Our speciality is low overhead teams, where every member is contributing concretely towards customer facing features. That means everyone is either doing development or design.

Roles like Project Manager, Business Analyst and QA are responsibilities which are shouldered by our business oriented developers or designers.

You may take the role of a Product Owner, making decisions on priority and scope.

Yes. We can adapt to your tools and processes. I.e. fully integrate into your existing team.

We follow best practices, perform code reviews, implement automated testing and continuous integration to ensure code quality and maintainability. All projects are not equal though and the level of automated QA will be determined on your need for quick feedback from the market.

Yes. We create easily understandable and maintainable code using well known frameworks which don’t require niche knowledge.

The runtime environments we can set up in your ownership from the get-go.

Every team has a partner involved in the project. Our developers have a proven track record of outsized throughput. Our culture is one of delivering features every day. That's why we prefer senior developers, but not seniors that are from slow moving enterprise environments.

We have fixed length iterations (usually 1 week), at the end of which you will be demoed the current progress. You will have access to team members through Slack, email and video calls and our regular meetings. In addition to this you will have access to our project management tools (Jira or Asana), which we update daily.

We love what we do and only employ people with a similar mindset. You ship faster by working with a small team where each developer is a focused on your business goals. With us you get direct access to everyone. This keeps overhead low and output high.

You are in control. We offer full transparency of progress and potential problems. We keep you informed and present options, but you make the decisions.

We value our client relationships and their product visions. Meet with us to see if we share the same conviction. We might be a good fit.