Andrew does hundreds of tasks at once — in the background, at night, on weekends. Categorizes documents, answers queries, generates reports, analyzes data. Your team sees results live, errors are handled automatically, every operation is logged.
Imagine a team of juniors with senior-level skills, working in fifty browser windows at once. No coffee breaks, no sick leave, no "I'll finish it tomorrow". That's Andrew — except without a desk, payroll, or national holidays.
Where a person processes one document per minute, Andrew processes five hundred. You come back Monday to 200 new emails — Andrew wrote 180 draft replies overnight and flagged 20 needing your decision. The monthly report that used to take two days of your life? Ready at 6:00 AM on the first of the month, as a PDF, with conclusions.
No magic. Underneath: solid engineering — FastAPI, Celery, Postgres, Redis wired to Claude 4.7 models (and cheaper ones, where they suffice). For you it looks different — a browser panel showing queue size, completed jobs, what's waiting for your "ok", and exactly what happened overnight while you slept.
Features that move your P&L. Not buzzwords — measurable outcomes.
Each task has a priority, deadline, and weight. Andrew decides what to run first — urgent and important goes to the strongest AI, bulk to the cheaper one. You see the full queue in the panel and can reorder it with one click.
Instead of one-by-one — dozens at a time. Andrew scales dynamically with the queue size. More workers during peak hours, fewer at night. You pay only for actual usage.
No need to wait for completion. Andrew shows the result as soon as it's ready — in the panel, on Slack, via email, or webhook to your system. Decide immediately, not an hour later.
Internet down? Provider API returned 500? Andrew retries with exponential backoff (1s → 2s → 4s → 8s). After 5 failed attempts — escalation to a human with full context.
Who, what, when, which model, how much it cost, what the result was. Every Andrew operation is logged immutably. GDPR and AI Act compliance — sorted. External audit? Logs from every single minute.
Andrew talks to your CRM, ERP, Slack, email, calendar, Trello, Notion, Google Sheets, Airtable. What happens — flows to your system. What your system changes — Andrew learns about it.
Każdy task ma swój kosztowy ślad. Możesz ustawić budżet dzienny/miesięczny — Andrew się w nim mieści. Drogie modele tylko gdy potrzebne, tańsze gdy wystarczą. Średnio 60–80% niższy rachunek niż "wszystko na Opusie".
Krytyczne decyzje (np. odpowiedź klientowi VIP, akceptacja faktury > 10 000 zł) zatrzymują się i czekają na zatwierdzenie. Twój zespół klika "ok" lub "popraw" — Andrew się uczy z każdej korekty.
Five steps that happen under the hood for every task.
From the panel, email, webhook, API, calendar, Slack. Andrew accepts from any source.
AI decides: priority, model to use, cost, deadline. Sorts into the queue.
A worker picks up the task, AI processes it, status streams to the panel.
Critical ones wait for human approval. The rest moves on instantly.
The result goes where it should — your system, email, file, integration. Audit log ready.
E-commerce, SaaS, kancelarie, biura księgowe — wszędzie tam, gdzie ludzie czytają i odpowiadają na hundreds podobnych pytań dziennie. Andrew odpowiada na proste, zatrzymuje trudne do człowieka.
Invoices, contracts, policies, statements, reports — categorization, data extraction, compliance validation. Andrew processes 1000 documents in the time a person handles 30.
Daily sales report, weekly KPI, monthly review — generated automatically, at a set time, in a fixed format, with conclusions. You return in the morning to a finished document.
Każda nowa wiadomość trafia do Andrew. Klasyfikuje: pytanie o status zamówienia, reklamacja, faktura, prośba o ofertę. Dla 80% pisze draft odpowiedzi z odniesieniem do bazy wiedzy firmy. Twój zespół przegląda drafty i klika "wyślij". Dla 20% trudnych — eskalacja do człowieka z pełnym kontekstem.
On the first of the month at 6:00 AM, Andrew pulls data from CRM, store, analytics, and ERP. Calculates KPIs, compares to the prior month, summarizes trends, detects anomalies. Generates a PDF with charts and text. At 8:00 AM the director gets an email with the finished report.
Andrew reads every PDF arriving in the accounting inbox. Extracts number, date, amounts, vendor; assigns to project/cost; checks compliance with the contract (e.g., whether the rate matches). Pushes to the accounting system, flags discrepancies. Humans just approve.
No — though we get the concern. Andrew takes routine: categorizing, classifying, drafting, sorting. Your people start doing what you really hired them for: talking to difficult clients, making decisions AI shouldn't, designing new processes. In practice, teams using Andrew don't cut staff — they stop hiring more as the business grows. That's the difference.
Every critical decision (invoice above amount X, reply to VIP client, refund approval) pauses for human review. The mass ones — e.g., classifying an email as "order status" — Andrew does itself, but leaves a trace: "92% confident, source here". If wrong, the operator clicks "fix" and the system learns from every correction. Within two months accuracy rises from 85% to 96%.
Andrew can run on-prem (on your servers), in your cloud, or hybrid. In every configuration, data never leaves your infrastructure. Communication with AI models goes through private endpoints (Anthropic, Azure OpenAI, dedicated local LLMs) without content logging on the provider's side. Full audit log, GDPR and AI Act compliance — included in the implementation.
Implementation is a one-time project cost (depends on scale). Monthly upkeep has two components: AI model cost (you pay for actual usage — €200–1000/month average for a mid-sized company) plus optional retainer for our team (from ~€700/month for 24h responsiveness). Most clients recoup the implementation cost in 3–6 months on team time savings alone.
With one process. The one your team loses the most time on, that nobody enjoys. Email inbox? Invoices? Ticket categorization? You pick one, we build Andrew for that specific case in 4 weeks, you test for a month whether it does what it should. If yes — we expand. If not — we stop, no long-term commitments.
Andrew isn't a script written between coffees. It's a production-grade system that scales to thousands of concurrent tasks, has a 99.9% SLA, and runs in environments from startups to mid-size enterprises.
Bezpłatna 45-minutowa rozmowa. Konkretny pomysł na pierwszy proces do automatyzacji — nawet jeśli nie zdecydujesz się na współpracę.