AI process automation for mid-sized companies
CodeGuides develops custom AI software that transforms Excel processes, documents, emails and ERP data into productive workflows.
- Automate Excel processes
- Evaluate documents and PDFs automatically
- Integrate AI securely into ERP, CRM and existing systems
Feel free to bring a specific process: an Excel file, document review, ERP workflow, or recurring back-office task.
- Custom software for mid-sized companies
- ERP and DMS integration
- AI document analysis
- Operation and further development
Selected projects and customers
When Excel, email and ERP slow down your processes
This is not an isolated case. It is everyday life in many medium-sized companies.
Offers, planning and evaluations are in individual files. It is often unclear which version applies and who last changed it.
Invoices, contracts, and forms are read, compared, and forwarded manually. This takes time and leads to errors.
Data is manually copied between ERP, CRM, email, and Excel. Every manual handoff takes time and increases the risk of errors.
Approvals happen over email, without clear ownership or documentation. It's difficult to track who approved what and when.
Processes, special rules and system knowledge are not documented. Vacation and fluctuation become an operational risk.
Available tools cover 80 percent of the need. The remaining 20 percent leads to workarounds and more Excel spreadsheets.
The best way to get started is with a process that today takes measurable time.
AI process automation is especially valuable when teams spend hours each month reviewing, transferring, searching, reconciling, or reporting on information.
- Less manual work
- Fewer errors from manual handoffs
- Faster turnaround times
- Relief for skilled staff
Free initial consultation, 45 minutes, concrete assessment of your process.
From data sources to a productive AI workflow
Existing data sources are connected through a structured AI workflow and transformed into usable results.
- Excel files
- PDF documents
- Emails
- ERP data
- CRM entries
- DMS documents
- Databases
- Reading and understanding
- Classify
- Check and validate
- Suggest
- Get approval
- Run automatically
- ERP update
- Structured report
- Dashboard entry
- Task or approval
- Customer portal update
- Documentation
Each step in the workflow is tailored to your process. AI is built into the workflow, not layered on top.
What we automate with AI and custom software
Five common use cases for midsize companies, each with a specific problem, a clear solution, and measurable results.
Automate Excel processes
Calculations and approvals are scattered across Excel files, with no clear version control.
We move the process into a web application with a database, user roles, validation, and optional AI support.
- No more version chaos
- Faster, documented releases
Evaluate documents automatically
Invoices, contracts and forms are checked and forwarded manually.
We automate the reading, classification and validation of PDFs and pass structured data to your subsequent processes.
- Less manual testing work
- Shorter lead times
Integrate AI into ERP, CRM and DMS
Data is manually copied between systems or is missing because there is no connection.
We integrate AI with your ERP, CRM, DMS, databases, or specialized systems. Your existing systems stay in place, with AI added where it can help.
- Less media breaks
- Better data availability
Making internal company knowledge usable
Process knowledge, guidelines and project knowledge lie in documents that no one can find quickly.
An AI assistant answers questions using approved internal sources. We configure access permissions and data sources.
- Less search effort and queries
- Faster onboarding
Automate back office processes
Data transfers, reporting, and internal audits take many hours each month.
We automate recurring steps so that specialists can concentrate on substantive tasks.
- More time for specialist work
- Lower error rate
Recognize any of these processes in your company? We can assess together whether an AI pilot makes sense.
Why a chatbot does not automate processes on its own
The question comes up often. Here is the direct answer.
- Answers questions, does not automate processes
- Usually works in isolation, without connections to your systems
- Does not automatically know your systems and data
- Does not take responsibility for processes or approval logic
- Integrated and connected to your systems
- Considers roles, rights and approvals
- Documents processing steps so they can be easily understood
- Writes data back to ERP, CRM and DMS in a controlled manner
The value doesn’t come from the chat itself. It comes from connecting AI, company data, interfaces and clear workflows.
How we start your automation project
Three steps from the first idea to the first productive solution. No big concept in advance, no long lead time.
Understand the process
We analyze your specific process, whether it involves an Excel file, documents, an ERP system, email, or a manual routine. This is a technical assessment, not a general conversation.
Assess automation potential
We assess technical feasibility, required data, system integrations, and realistic benefits. You’ll get a clear assessment, with no promises.
Develop MVP or pilot
A first production-ready solution for a clearly defined process. You see early on what it can do and can make further decisions based on real-world experience.
Practical ways to get started
Three common starting points, each with clear outcomes and rough cost estimates.
Automation check
For companies that want to know which processes are suitable.
- Assessment of suitable processes
- Assessment of technical feasibility
- Rough effort and prioritization
- Recommendation for a pilot or MVP
AI pilot or MVP
For a clearly defined process with real productive use.
- Productive first AI workflow
- Real data or test data
- First system integration
- Resilient basis for expansion
Custom business software
For larger platforms, portals and long-term process automation.
- Custom web application
- Multiple interfaces and roles
- Roles and rights concept
- Operation and further development
These are estimates based on the process, data, integrations, and scope. In the initial consultation, you’ll receive a realistic assessment.
Book an appointment
For companies ready to discuss a specific process. A 45-minute initial technical consultation.
Choose a time on the calendarSend request
For companies that would like an initial written assessment. We will respond within one business day.
Make a requestExamples of potential projects
Three common starting points drawn from the experience of mid-sized companies.
Automate the quotation process
Excel calculation, email approval and ERP transfer become a guided workflow with validation, approval and automatic data transfer. Fewer manual steps, more traceability.
Accelerate document review
PDFs are read automatically, relevant data is extracted, and anomalies are flagged for review. Processing takes minutes instead of hours, and results go straight to the next system.
Making internal knowledge usable
Employees ask questions about policies, projects, or processes and get answers from approved internal sources, with clear access permissions and controlled data sources.
What you can gain from AI process automation
No abstract promises. These advantages are clearly visible in everyday working life.
Less search effort
Knowledge becomes centrally accessible. Employees find guidelines, processes and project information without asking others.
Fewer queries
Guided processes and clear documentation reduce internal coordination loops.
Fewer errors
Data is not copied multiple times. Clean interfaces eliminate media breaks between systems.
Faster processing
Documents are automatically pre-structured. Testing and approval steps run faster.
Better controls
Status, utilization and bottlenecks become visible. Decisions can be made based on data.
More scalability
Processes no longer depend on individual employees. You can grow without increasing headcount at the same rate.
Who is AI process automation suitable for?
Custom AI process automation isn’t an off-the-shelf product. Here are some clear criteria to consider.
Suitable
- Existing manual process with recurring effort
- Data, documents or systems exist that should be connected
- An internal point of contact who knows the process and helps shape it
- Goal: Measurably improve efficiency, quality or transparency
- AI should be used safely in production, not just tested
- Willingness to analyze and adapt existing processes
Not suitable
- Pure AI gimmick without any concrete business process
- App idea without a validated market or process
- No budget for implementation and operation
- No specific person responsible internally
- No willingness to analyze existing processes
Unsure whether your plan is right? In the initial consultation, we will tell you openly whether and how a project makes sense.
Technical implementation from a single source
CodeGuides develops, integrates, and operates your solution. No concept without implementation, and no launch without ongoing operations.
Backend, APIs and web applications, developed for your specific process and your existing systems.
AI is integrated into existing systems, with roles, permissions, and comprehensive logging.
No project without realistic benefits. We will tell you clearly what is possible and what is not.
Start with a production-ready version for one clearly defined process, then expand gradually based on real-world experience.
Monitoring, maintenance, security updates, and ongoing development are all part of the solution.
Data storage in Germany or the EU, clear access concepts, logging and deletion concepts.
Quick automation check
Answer five questions. Three or more yes answers indicate strong potential for AI process automation.
Frequently asked questions about AI process automation
What is AI process automation?
AI process automation uses AI-powered software to automate or support manual business processes. Examples include extracting information from documents, processing ERP data, and turning Excel-based processes into structured workflows. Unlike a basic chat tool, it’s an integrated software solution with system connections, roles, logging, and ongoing operations.
How much does an AI process automation project cost?
A structured potential analysis typically costs €1,500 to €5,000. A first pilot or MVP often costs €15,000 to €60,000, depending on integrations, data, and scope. These are estimates; in the initial consultation, you’ll receive a realistic assessment of your specific project.
How long does a first AI pilot take?
For a clearly defined process with existing data and established integrations, four to eight weeks is a realistic timeline for a first production-ready MVP. The exact timeline depends on complexity, data availability, and the availability of your internal contacts.
Can existing Excel processes be automated?
Yes. Excel-based processes such as calculations, approvals, and reporting can be moved to stable web applications or automated directly. The solution can include a database, roles and permissions, validation, and AI support as needed. Automating Excel processes is one of the most common starting points for mid-sized businesses.
Can PDFs and documents be evaluated automatically?
Yes. Invoices, contracts, reports, delivery notes and other PDFs can be automatically read, classified, checked and further processed in a structured manner. The results are passed on to your subsequent processes or systems.
Can AI be integrated into our ERP system?
In most cases, yes. Modern ERP systems typically offer APIs or export interfaces that allow AI-powered workflows to connect to them. We’ll assess whether and how this is possible with your system during the initial consultation.
Can the solution be implemented in compliance with the GDPR?
Yes. We build solutions with a GDPR-oriented architecture, including data storage in Germany or the EU, clear access controls, logging, and data deletion procedures. The specific requirements depend on your process and the data involved.
Does data need to be sent to external AI providers?
No. Depending on your requirements, we can use external AI providers with data protection agreements, European alternatives, or locally hosted models. We’ll work with you to determine the right option.
Does CodeGuides provide ongoing operations and further development?
Yes. We support projects after launch with monitoring, maintenance, security updates, new features, and AI workflow optimization. This helps keep your solution productive and adaptable over the long term.
Can we start small and expand later?
Yes, that’s what we recommend. A clearly defined pilot for a specific process delivers results faster than a broad, all-encompassing concept. You can decide how to proceed—or whether to proceed at all—based on real-world experience.
CodeGuides develops apps for consumers and businesses, with a primary focus on B2C apps. Our in-house team in Germany provides product planning, Flutter development and long-term operations, alongside custom software, AI automation and local AI infrastructure.
Make a request
A brief description is enough. During the initial consultation, we’ll work with you to determine whether the process is a good fit for AI automation.
Schedule a meeting
Choose a time directly on the calendar. A 45-minute initial technical consultation, with no standard sales pitch.
- 45 minutes Google Meet
- Expert assessment of your process
- Technical feasibility and realistic effort
- Clear recommendation for next steps
Project questions and practical answers
How do you implement AI business process automation?
Map the process, inputs, exceptions and responsible people before selecting a model. Use deterministic rules for predictable decisions and AI for tasks such as classification or extracting information. CodeGuides integrates the workflow with existing systems, tests it against representative data and adds human approval where errors matter. Measure quality, processing time and operating cost before expanding.
Which process automation use cases suit a medium-sized business?
Start with repeatable work such as routing incoming requests, extracting invoice fields or preparing service replies. Choose a bounded process with accessible data and a measurable baseline. Estimate integration and review effort as well as potential benefits. Run a pilot with human checks and compare error rates and total cost before approving broader implementation.
Where can AI support back-office automation?
AI can classify incoming documents, suggest account assignments or prepare responses, while deterministic workflows handle approvals and system updates. Define who checks uncertain results and who can change records. Connect ERP or document systems through controlled interfaces, retain an audit trail and test duplicate inputs, exceptions and recovery before unattended operation.
How can a medium-sized business automate document analysis?
Define document types, required fields and acceptable error rates. An implementation may combine OCR, extraction models and validation against business records. Route uncertain or sensitive results to a reviewer, and retain the original document and decision history. Test on representative scans and layouts; processing a clean demonstration PDF does not establish production accuracy.
What does ERP workflow automation require?
Identify the authoritative ERP records and the events that should trigger actions. Use supported APIs, stable identifiers and permission-limited service accounts. Make updates idempotent so retries do not duplicate orders or invoices. Add approval steps for consequential changes and reconcile failed jobs. AI may interpret unstructured input; it should not bypass ERP validation.
How do you approach automating complex Excel processes?
Inventory formulas, macros, data sources and the people who resolve exceptions. Separate calculations that can be implemented deterministically from text interpretation that may benefit from AI. Build regression cases from known spreadsheets and compare results before replacing the workflow. Preserve exports where users need them, and assign ownership for ongoing business-rule changes.
How do you move a manual process to automation?
Observe the actual workflow, including corrections and exceptions, then document its inputs, decisions and outputs. Establish a baseline for time and error rates. Automate a bounded stage first and provide a manual fallback. Review the result with process owners before extending it; a poorly defined process usually needs clarification before software can reliably automate it.
How can an AI assistant support business process automation safely?
Define which tasks the assistant can read, propose and execute. Use narrowly scoped tools, role checks and explicit approval for consequential writes. Log tool actions and preserve a human recovery path. Test incorrect instructions, missing information and unavailable systems, not just successful conversations. Production integration requires these controls beyond a standalone chat interface.
What belongs in a data processing automation workflow?
Define input contracts, validation rules and the destination system. Use repeatable transformations, duplicate detection and traceable errors so failed batches can be rerun safely. AI is optional and should only be used where unstructured input requires interpretation. Check output quality against representative samples and establish retention, access and operational ownership.