AI automation for business
AI automation for business hands repetitive work to AI agents — software that reads documents, grasps context and decides. Saitami builds such agents on GPT-4 and Claude, wires them into your ERP, CRM and email, and you get a digital employee that never sleeps.
What AI automation includes
Unlike RPA that repeats fixed steps, business AI agents understand language and decide at a junior-employee level. What we ship:
- Email triage and classification. The agent reads Gmail or Microsoft 365, detects type (lead, complaint, invoice, spam), extracts customer and amount, and creates a ticket in CRM or ERP.
- PDF and invoice reading with OCR + LLM. Scanned docs go through OCR (Tesseract / Azure Document Intelligence), then an LLM extracts counterparty, tax ID, date, line items and VAT. The result lands in your accounting software.
- AI agent for inbound leads. A bot replies to new inquiries within a minute — asks 3-5 qualifying questions, scores readiness, writes to CRM, and pings sales only for hot leads.
- Auto-generated reports. Weekly and monthly reports a human used to build from 4 spreadsheets are written by the agent in 2 minutes — with summary, charts and auto-email to management.
- Internal AI assistant over your knowledge base. A Slack or Teams bot trained on your internal docs via RAG. Employees ask in natural language, the agent answers with a citation to the source.
- ERP, CRM and accounting integration. We wire agents into HubSpot, Pipedrive, Odoo, SAP and Microinvest — two-way, via official APIs or direct DB.
Who this is for
Accounting and legal firms
A firm processing 200 invoices and 80 contracts a month moves 60-70% of manual entry to an AI agent. Documents are read, classified and presented pre-filled for human review — not written from scratch.
E-commerce stores
The AI agent classifies inbound queries on your site and Facebook — order, refund, product question — and answers 70% of them with relevant info from the catalog. Only edge cases reach a human.
Manufacturing
The agent reads shift reports, customer complaints and defect logs, groups them by root cause (material, operator, machine) and flags deviations. What QA did weekly happens in real time.
How we build AI agents
1. Process mapping. We map repetitive manual tasks — volume, handling time, cost of error. We pick 2-3 processes with the best ROI, not everything at once.
2. Tech stack. GPT-4o or Claude 3.5 Sonnet for reasoning, Python or Node.js orchestration, n8n for workflow visualization (or a custom engine for complex cases), and Postgres with pgvector for RAG.
3. Integrations. We connect agents to Gmail / Outlook, Microsoft 365, your ERP, CRM and accounting software. Where no official API exists, we use a headless browser or direct DB work.
4. Pilot, evaluation, production. A 2-week pilot on real data, measure precision/recall and hallucination rate, tune prompts and guardrails. Only after >95% accuracy on a golden dataset do we ship — with human oversight in month one.
Why Saitami for intelligent automation
faster handling of repetitive tasks vs. manual process
human-hours saved per employee per week with an AI workflow
starting investment for your first AI agent in production
We do not resell platform licenses. We build your own agent with your data, your prompt, your control — on a proven LLM. The "AI add-on inside SaaS" alternatives work until the vendor raises prices.
Frequently Asked Questions
How is an AI agent different from regular automation?
Classic RPA or Zapier-style workflow runs on fixed rules — "if the email contains word X, do Y". Business AI agents use LLMs (GPT-4, Claude) to understand meaning, context and nuance. The same agent correctly handles both "I need an invoice" and "I need a document for accounting" — without 200 if-else rules. That is the difference between a script and a junior employee.
Where does the data the AI uses come from?
From your own systems — Gmail or Microsoft 365 for email, ERP for invoices and orders, CRM for contacts, file server or SharePoint for documents. The RAG index is built from your internal documentation. The AI agent never invents — it answers only over the sources you provided, with a citation linking back to the original record.
Is it safe for confidential data?
For sensitive clients we use enterprise endpoints on OpenAI and Anthropic with zero data retention — data is not used for training and not stored on their side. For stricter cases (banking, healthcare) we deploy open-source LLMs (Llama 3, Mistral) on your server or an EU cloud. GDPR compliance is default, not an extra.
How much does AI automation for business cost?
Starting investment is €3,500 for the first agent in production — covers analysis, prototype, integration with one key system and a 4-week pilot. Mid-size projects run €8,000-€15,000 for 2-3 connected processes. Monthly run-cost (LLM API plus hosting) is typically €100-€400 depending on volume. ROI usually returns in 4-7 months.
Ready for your first AI agent?
Show us the 2-3 processes that eat the most of your team's time. We come back with a concrete ROI estimate and a pilot plan.
Audit my processes for AI →Related: AI chatbot for website, WhatsApp Viber automation, business process automation and API integrations. AI automation for business is strongest when built on clean data and solid integrations.