What problems does AI automation solve in companies?
Preparing a quote ties up sales and engineering for weeks. Projects slip away because of missed deadlines.
Employees lose 40+ hours a month retyping data between systems.
Invoices wait for approval because the right person is unavailable.
Sales reports are produced once a week because collecting the data takes half a day.
You want to adopt AI, but you fear customer data will end up on external servers.
A voicebot could handle 80% of phone inquiries. Instead, an employee does.
AI automation makes sense wherever there is a repetitive, data-driven process.
And a person who loses time on it.
Healthcare and pharma
Patient data and medical confidentiality cannot go to an external AI cloud.
We deploy Polish AI models running locally. The data stays with you.
Finance and accounting
An accountant spends 3 hours a day describing invoices by hand. KSeF (Poland's national e-invoicing system) requires tagging, and a mistake costs a correction and time. AML processes and regulatory reporting take up a whole department.
We integrate accounting systems with the CRM without manual retyping. Invoices are tagged automatically, AML is reported without spreadsheets.
E-commerce
Price monitoring, product descriptions, handling inquiries: volume grows, the team does not.
Price monitoring and 24/7 support deployed in 2 weeks. ROI often before the end of the first month.
BPO / Contact center
Ticket prioritization, and volume grows faster than the team.
Voicebots, sentiment analysis, automatic routing. A human gets only what needs a human.
Real estate and hospitality
Repetitive tenant and guest inquiries, manual contracts, tracking deadlines.
Voicebot -80% human interventions. Automated contracts and deadline monitoring.
B2B with a quoting process
Preparing a single quote involves several people for weeks.
Transcription, PDF calculator, inquiry completeness monitoring. Case study: -108 h/month.
Manufacturing and operations
Project tracking, escalating delays, unstructured documents.
Automatic tickets, ERP integration, processing of emails and PDFs.
Education and NGOs
Small budget, lots of repetitive documents and communication.
AI for letters, reports and grant applications. Low-cost open-source solutions.
Sensitive data / compliance
Professional secrecy, the AI Act, GDPR: every technology decision has to be lawful.
Local models, DPA as standard, GDPR and AI Act compliance analysis.
Insurance and finance
Agents lose hours comparing policies by hand, filling in applications and handling claims. Every mistake is a compliance risk.
AI compares policies, fills in applications and generates quotes from customer data. Claims handling gets 60–70% shorter.
Which business processes can be automated with AI?
8 areas where repetitive work is replaced by working AI systems.
Sales and quoting automation
The salesperson gets a call summary in 30 seconds, with transcription running in the background. A quote calculator produces a PDF from project parameters without involving the technical team. Lead scoring and pipeline tracking happen without manual CRM updates.
Finance and accounting automation
Invoices reach the accounting system without a click: fetched, categorized and archived automatically. The accounting software stays in sync with the CRM. The financial report builds itself, and an alert arrives when cash flow departs from the norm.
HR and recruitment automation
A job posting is ready in a minute. CVs are sorted by your criteria before HR opens the inbox. Candidates get an automatic reply, and handling time drops by 70%. Onboarding shrinks from 3 days to 4 hours.
AI chatbots and voicebots
A customer asks a question at 2 a.m. and the chatbot answers from your company knowledge base without any employee involved. A voicebot picks up calls and escalates only the cases it cannot handle itself. Sentiment analysis spots frustrated customers and hands them to a human.
ASAPChat: our AI chat for e-commerce →E-commerce and marketing automation
Competitor prices are tracked in real time and your offer adjusts automatically. ASAPDevs clients see +25% conversion on average after deploying price monitoring. Product descriptions and SEO content are generated without a copywriter. Campaigns are planned and reported without manual work.
Operations and IT automation
A service ticket opens when a failure is detected, on average 12 minutes before the customer reports it. Unstructured documents (emails, PDFs, recordings) are processed and indexed without manual intervention.
Price, stock and alert monitoring
Stock levels, competitor prices and system availability are tracked around the clock. An alert goes to email, SMS or Slack when a metric crosses a threshold. You get the signal before the problem reaches a customer.
Automated website testing
After every deployment the site is tested automatically: forms, purchase paths, links, responsiveness. The error is caught before the customer sees it, not by the customer. The results report goes to the team without anyone running tests by hand.
How does an AI automation rollout work?
6 stages. Each ends with a concrete, measurable result.
Results, not promises.
Quoting process automation
Product complexity meant both sales and engineering had to be involved in every quote. Preparation time: several weeks. The company started losing contracts because of missed deadlines.
We mapped the whole process and deployed four components: AI transcription of customer calls, inquiry completeness monitoring, a quote calculator that generates a PDF from project parameters, and one-click sending.
| Metric | Result |
|---|---|
| Rollout time | 4 weeks |
| Time saved | 108 h / month |
| Return on investment | after 3.5 months |
Voicebot for an apartment rental company
The owner of rental apartments took repetitive calls from guests every day. The same questions, the same time.
We deployed an AI voicebot that picks up calls, analyzes the question and answers from a knowledge base about the property. When it has no answer, it forwards the call to an employee.
AI deployment results in numbers
| Process | Result |
|---|---|
| Invoice processing | 80% automation, -60% reconciliation time |
| Sales email handling | -70% handling time, full GDPR compliance |
| Competitor price monitoring | +25% conversion through dynamic adjustment |
| System monitoring + alerts | Failures detected 12 min on average before the customer reports them |
| Employee onboarding | From 3 days to 4 hours |
| Phone support in hospitality | -80% human interventions |
| B2B quoting | -108 h/month, ROI after 3.5 months |
Data from ASAPDevs deployments 2022–2025. Results may vary depending on scale and industry.
Is AI adoption safe for company data?
Yes, provided the model is chosen properly. We work with commercial models (Claude, GPT, Gemini) and open-weights models (Llama, Qwen, Mistral), and we will deploy any other, including the Polish Bielik and PLLuM. For companies processing sensitive data (patients, customers, documents covered by professional secrecy) we deploy models locally on the client's server. The data does not leave the organization.
We will deploy any model, and we choose it by testing on your data. For sensitive data: on-premise, an open-weights model or a private instance of a commercial model. No provider trains on your data without your consent.
You do not need to ask. A data processing agreement is standard in every deployment. We verify each provider's policies before launch.
When data cannot leave the company
We also build AI systems on models run on the client's server or in the EU.
AI automation without replacing the systems that work
We do not replace your accounting software, CRM or email. We add automation next to them and follow your rules.
Frequently asked questions.
30 minutes. One process. A concrete assessment.
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