Every inquiry lost in a chat is a deal someone else closes. I build the back office where nothing gets lost.
One system for inquiries, clients and reports. Your managers stop retyping and start selling, and you see the money in numbers. Built around how you sell, on your server.
- Inquiry
- Deal
- Payment
- Report
- Your decision
Not in the market. In the hours between the inquiry, the spreadsheet and the manager.
of companies never answered a web inquiry at all. The average reply took 42 hours.
Harvard Business Review, 2011of small EU firms work in a CRM, against 65% of large ones. For BI it is 11% against 69%.
Eurostat, 2025a week saved per person by workers who already use generative AI.
Federal Reserve Bank of St. Louis, 2025Large companies bought these systems long ago. A team of ten can now have the same, built for its own process.
What the chats and spreadsheets cost you
Put in your own numbers. Nothing leaves this page.
What changes in the money
Every inquiry from the site, chats and calls lands in one place with an owner and a deadline. Nothing waits in someone's phone until the client buys elsewhere.
Voice notes and forwarded chats become records, reports and documents read themselves, overdue tasks come as reminders. The hours go to selling, not retyping.
Clients ask in their own words or send a map screenshot and get the two or three options that fit. Fewer messages before a viewing, a booking or a deal.
Where deals stall, which source brings paying clients, who carries the week. You decide from numbers, not from the last conversation.
Need an AI Sales Manager that answers inquiries on your site day and night? It is on the AI Inbound page →
One system instead of five tools that do not talk
Office workers switch between apps about 1,200 times a day and lose almost four hours a week getting back on track.
The inquiry lands in the CRM, agents keep the record clean, you see the week in numbers. One contact for all of it, it runs on your server, the source code is yours.
From call to production · 3–14 days
The routine your managers do today, done by agents
- Manager
- writes the end-of-day report in free form; the agent turns it into numbers: leads, follow-ups, blockers, plan for tomorrow.
- Team lead
- gets a morning brief, overdue tasks and stalled conversations without asking.
- Operations
- incoming posts and documents are sorted, checked, translated and turned into structured cards.
- Finance
- payment slips are read before a person confirms them.
- HR
- candidates answer follow-up questions, send files, get a score against the role.
Running today in HelpRent Phangan, the operating system I built for a real-estate agency, and in HelpRent Da Nang.
issues resolved per hour by support agents with an AI assistant. Novices: +34%.
Brynjolfsson, Li, Raymond · NBER, 2023time on business writing tasks with an AI assistant, at 18% higher quality.
Noy, Zhang · Science, 2023Clients search in plain words. The formula does the matching.
- 01 · The request
“2 bedrooms near the beach, up to $800, from March”, or a screenshot of a map
- 02 · AI reads it
budget, area, size, dates become criteria, in any language
- 03 · The formula ranks
every listing scored on the same weights, nothing hidden
- 04 · The client gets
the two or three that fit, each with its reasons
The manager sees why each option is on the list. When the market changes, you change a weight, not a model.
Built for HelpRent Phangan, and again for the whole Da Nang rental market, where the assistant Mai also searches by a screenshot of a map.
Systems AI assistants can read, and pay for
On HelpRent Da Nang this is not a plan, it is an endpoint.
The same principle makes your company visible to AI assistants: AI Inbound →
What it costs
Three scopes, each with a starting price. The exact figure for your task comes after a short call. Outbound and AI Inbound are priced separately.
- Website or CRM on your server
- Telegram notifications
- Source code delivered
- 1 revision
support quoted with it
- Everything in Core
- BI and manager dashboards
- Integrations with your stack
- 2 revisions
support quoted with it
- Website + CRM + BI
- AI agents for your team
- Search and matching
- MCP server and API if needed
- 3 revisions
support quoted with it
- Core
- Website or CRM on your serverYes
- Telegram notificationsYes
- Source code deliveredYes
- BI and manager dashboardsNo
- Integrations with your stackNo
- Website + CRM + BI togetherNo
- AI agents for your teamNo
- Search and matchingNo
- MCP server and APINo
- Revisions1
- Business
- Website or CRM on your serverYes
- Telegram notificationsYes
- Source code deliveredYes
- BI and manager dashboardsYes
- Integrations with your stackYes
- Website + CRM + BI togetherNo
- AI agents for your teamNo
- Search and matchingNo
- MCP server and APINo
- Revisions2
- Full System
- Website or CRM on your serverYes
- Telegram notificationsYes
- Source code deliveredYes
- BI and manager dashboardsYes
- Integrations with your stackYes
- Website + CRM + BI togetherYes
- AI agents for your teamYes
- Search and matchingYes
- MCP server and APIYes
- Revisions3
Four things owners ask
- How do I know it paid off?
- The dashboard shows it: how many inquiries came in, how fast they were answered, where deals stall. You compare the month before and the month after.
- Will my team actually use it?
- It is built around how they already work. Managers keep writing in Telegram; agents turn that into records.
- We already have a CRM.
- I connect to it, or move the data into a system that fits your process. The data stays yours.
- Who owns the code and the data?
- You do. It runs on your server and the source code is handed over.
Tell me how your business runs today
Where inquiries arrive, where clients and deals are kept, who writes the reports. I'll reply in writing with what to build first.