AI Engineering: Scalable Bots & Automations

From ideas to AI solutions

Whether it's a chatbot, process automation or an individual ML model: Our AI engineers bring your AI idea from concept to production readiness in a flash. From proof of value to rollout, we deliver AI that scales and works from the start.
AI Strategy Consulting - taod.ai
A selection of some of our AI engineering customers

Our AI engineering packages:
Built to fit, designed to expand

Quick start or complex AI solution. Our engineering packages are tailored to your needs. From proof of value to custom models and dedicated AI engineers. We support you flexibly, but always with a focus on clean data, lean processes and measurable business benefits.

Kickstart

Rapid Prototype

10-day PoC
from chatbot to automation and more
functional prototype and demo
quick evaluation of your use case
basis for scaled, integrated solution
Kickstart

Rapid AI Proof

Do you have an idea or challenge, but still not sure whether AI will really help you here? With the “Rapid AI Proof”, you'll know in less than 10 days.

With your data and infrastructure, we'll show you whether AI use case is technically feasible and can create real added value. And above all, what is the best way to proceed afterwards.
Pilot

MVP
Accelerator

reach an AI MVP in 4 to 6 weeks
optimal feedback loops for iterative improvement
KPI dashboard for key insights
direct added value as an MVP
Pilot

MVP
Accelerator

Do you have a well-thought-out AI use case to implement? With our MVP Accelerator Package, we bring your idea to an applicable AI solution in just 4-6 weeks.

Automated monitoring provides clean metrics, while a selected user group tests the system in everyday life. You can see live the business impact of the solution and thus lay the basis for the subsequent scale step.
Scale Up

Enterprise-ready AI

from 6 weeks until your scalable solution is ready
seamless integration into existing systems & platforms
impact monitoring through KPI tracking & cost control
Scale-Up

Enterprise-ready AI

Your MVP is convincing — now the Enterprise Boost is coming: In 6 to 18 weeks, we will turn it into a stable, secure and scalable AI service.

With automated deployments, complete documentation and a KPI dashboard, you can keep an eye on performance, costs and impact at all times.
Team Up

AI Engineers on Demand

flexible capacities, bookable in hours, days or weeks
senior expertise in GenAI, LLMs, MLOps, Cloud & Data Engineering
seamless integration into your team, project, processes & tools
Team Up

AI Engineers on Demand

Do you need to compensate for a lack of capacity or special know-how? Our AI experts get straight into your sprints remotely or on site — with best practices on code quality, CI/CD, security, and cost optimization.

Flexibly scalable, budget-controlled and ideal for feature peaks, vacation gaps or rapid knowledge transfer.
No suitable package included? No problem!

Whether it's a chatbot, process automation or much more: Let us know how we can support you.

AI Engineering Solutions

Our AI Engineering Solutions are standardized AI services that we implement step by step with your team. From the first workshop to prototypes to stable operation. This gives you solutions that are suitable for everyday use, have a measurable effect and fit neatly into your systems.

AI Analyst

From data chaos to decision insights: Let teams generate ad-hoc analyses and KPIs directly via natural language input

Services & components:

data discovery & KPI definition

RAG/SQL agent for ad hoc questions

monitoring & guardrails

pilot production

Customer Service Chatbot

24/7 answers, lower ticket load, higher satisfaction — the bot solves standard cases and transfers seamlessly to agents.

Services & components:

use case & intent design

knowledge connection (RAG)

CRM/help desk integration

bot analytics & optimization

LabMind - R&D Assistant

Finds knowledge in internal sources, summarizes precisely, cites cleanly — ideal for sales, support & all specialist departments.

Services & components:

data collection & vector index

retrieval strategy

citation and source documents

RAG evaluation

Process Automation

Connect tools, trigger workflows, eliminate routines — from email routing to report creation to greater efficiency.

Services & components:

process screening & prioritization

LLM-based automations/agents

integrations (APIs, webhooks)

security/compliance checks

Voicebot

The voicebot understands & answers concerns, qualifies leads and transmits to sales or support.

Services & components:

telephony/SIP setup

realtime LLM orchestration

intent & dialog flows

live agent handoff

Safe GPT

Enterprise-secure GenAI — EU-hosted models, SSO, cost control & governance for regulated environments.

Services & components:

policy & risk framework

AI-act readiness (roles, documentation, logging)

EU region operation, SSO & DLP

AI Case Studies

Successful AI engineering from practice

Lächelnder Mann mit Glatze und Bart in weißem Hemd vor Holzwand.
Christian Weise
Chief Service Officer
microtech
“The chatbot helps us provide quick support exactly where no personal support is required. This allows our users to get answers to common questions 24/7 — and our support team can focus entirely on complex issues. This not only improves service, but also satisfaction on both sides.”
Junge Frau mit langen braunen Haaren, die einen weißen Blazer und weiße Bluse trägt, lächelt vor grauem und beigem Hintergrund.
Vanessa Kremer
Lead Data & Analytics Chapter
With the AI Analyst, real data competence is created. Our data team is noticeably relieved and data-based decisions become a natural part of daily work.
Microtech logo in front of a headset
Case Study

A chatbot for more efficiency in customer service

ERP software company microtech uses taod.ai to automate parts of its customer service with an AI-based chatbot. In our case study, follow the course of the project from idea to implementation and a convincing result.

Case Study

With the AI Analyst Query KPIs & trends via chat

Aachen's basic assets are 100% self-service BI thanks to our AI Analyst: Employees get direct access to KPIs and trends via ad hoc queries in teams. Completely without a data team, BI knowledge or complex dashboarding.

AI Engineering: From Idea to Practice

Our engineering for your AI vision

Theory Off, Hands On: We deliver results, not just ideas. To do this, we build well-founded AI solutions that run in your company: stable, efficient and with real results. From setting up your data infrastructure to go-live. Whether with chatbots or custom models: Our solutions grow with you.

Clean data & processes are the holy grail

We ensure structured, valid and automatable data pipelines. They are the stable foundation for every AI solution. Reliable models can only be created from clean data and well-thought-out processes.

Tools & technologies that scale

We rely on tools that not only work today, but also grow with your requirements. From the first application to a scalable platform. Our tech stack is designed to deliver quickly, securely, and future-proof.

Full focus on project & output

For us, the focus is on the result. We think along with you right from the start: from the idea to the running system. The goal is not just an MVP, but a solution that improves your everyday life, runs productively and creates real business impact.

Common questions (FAQ)

How do I actually implement my AI idea with you?

You implement your AI idea with us from the first proof of value to a production-ready solution. Depending on your needs, we support you from a quick prototype to an MVP to a scalable enterprise solution.

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We don't start with technology, we start with your problem. Together, we clarify what the solution must be able to do, where it should create added value and what a useful first step looks like. Depending on the level of maturity, we develop a proof of value, an MVP or a production-ready solution. It is important to us that not only does something work technically in the end, but that it can also really be used in your company. So you don't have to come to us with a ready-made concept. We help you turn a good idea into a solution that works.

Which AI engineering package is right for my project?

That depends on how far along your project is. If you want to check feasibility first, you need something other than an MVP, a productive solution, or additional engineering support.

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If you want to find out first whether a use case with your data and systems can even be implemented sensibly, a quick proof is the right start. If your project is already clearer and you want to build something useful in a short time, an MVP format is better. If initial solutions already exist and it is now about stability, security, operation and scaling, a production-oriented approach makes sense. And if you simply lack time or special know-how internally, we will provide you with targeted support with additional engineering capacity. So you don't need the biggest package, but the one that fits your current situation.

How does an AI engineering project typically work with you?

We work in a structured way, from target vision to validation and development to integration into your existing systems. This does not create an isolated prototype, but a realistic way to use it.

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At the beginning, there is always the question of what exactly you want to solve. Based on this, we look at which data, systems and processes are relevant and where a useful start lies. We then check feasibility and benefits, develop a proof or an MVP, depending on the format, and then translate the solution into stable technical processes. This is not only about the model itself, but also about interfaces, data flows, monitoring, documentation and operation. In the end, this is exactly what makes the difference between a demo and a solution that really works in everyday life.

How quickly can I get a first result with you?

Usually fast when the goal is clear enough. We consciously work so that you get something tangible early on and don't get stuck in long concept phases.

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If you want to check technical feasibility and potential first, we can create a reliable initial result early on. If your use case is already clearly outlined, we will guide you to an applicable solution within a compact time frame. If your goal is a production-ready implementation, more time goes into stability, integration, and operation. We don't promise you an unrealistically short abbreviation. But we avoid exactly what many AI projects fail to do: planning too long without real progress. Our focus is on making sure you learn quickly enough and at the same time build something that has substance.

How do you integrate your AI solution into my existing IT landscape?

We don't build AI solutions next to your IT, but for your IT. For us, integration is therefore part of implementation and not an issue that only comes up at the end.

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An AI solution is of little use to you if it looks good in a demo call but doesn't work in your real processes. That's why we consider early on how the solution fits into your system landscape, for example via APIs, webhooks, existing platforms or other technical interfaces. At the same time, we pay attention to security, access logic, monitoring and operation. For you, this means: We don't simply develop something isolated, but a solution that should exist in your real environment. This is exactly what determines whether AI creates benefits in companies or just acts like innovation.

What exactly do I get from you in the end?

You won't get an abstract AI concept from us, but a concrete result that you can continue working with. Depending on the format, this is a validated proof, a usable MVP, a production-ready solution, or targeted technical support for your team.

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We don't provide you with a loose idea paper, but a result with practical relevance. This could be a functional prototype, an MVP, a stable and scalable AI solution, or a clearly defined technical advance in your existing setup. Depending on the project, this also includes monitoring, documentation, KPI orientation and controllable operation. What counts for us is that in the end you not only know more about AI, but also have something in your hand that is validated, usable or directly connectable for the next step. Engineering should be measured against this.

Event: AI Networking for Leaders (Stuttgart)

Headquarters Cologne

taod Consulting GmbH
Oskar-Jaeger-Strasse 173, K4
50825 Cologne
Hamburg location

taod Consulting GmbH
Alter Wall 32
20457 Hamburg
Stuttgart location

taod Consulting GmbH
Schelmenwasenstrasse 32
70567 Stuttgart