Intake and first screening
WhatsApp forms and bots that ask for missing information, classify the inquiry and pass it to the right person with context.
First we see how the work moves today. The building blocks repeat across organizations; the value is in the passage between the systems already running.

Who performs each action, where the information lives, where decisions are made and what happens when a detail is missing.
From that flow the suitable components are chosen: rules, integrations, a working interface or an AI capability, and how they fit the existing systems.
WhatsApp forms and bots that ask for missing information, classify the inquiry and pass it to the right person with context.
Intake, OCR, transcription, search and conversation with internal material, including a way back to the source the answer rests on.
Screens that gather status, payments, tasks or exceptions from the systems that already hold the data.
A tool that reads information, prepares a draft or updates a system inside clear boundaries and stopping points.
Email, CRM, Google Workspace and other services, with failure handling and a record of what happened.
Infrastructure for businesses that manage numbers, conversations, files and groups across several accounts, according to the platform rules.
An incoming inquiry, a document, a payment or a management question. The system connects them.
A command dashboard cross-referencing payment stages with SAP, alongside a leads and signatures portal, advanced document search, and real-time status updates for residents.
Instead of manually piecing together the picture from multiple sources, the team manages the project from a single screen reflecting progress and bottlenecks.
A smart WhatsApp agent that receives incoming inquiries, collects missing data from the client, and forwards an organized file to the office, accompanied by an automated refinance viability check.
The advisor starts the workday with complete, ready-to-use data, eliminating time wasted on lengthy data-extraction correspondence.
A natural language interface connected directly to customer data, inventory management, and the order system within the company's existing CRM.
Management receives precise, real-time answers to business queries without navigating screens or generating complex reports.
A document processing platform featuring sync, OCR, transcription, and a semantic search engine that cross-references information across the entire archive.
Lawyers query the file in natural Hebrew and receive answers backed by direct citations to the relevant paragraphs in the source documents.
An internal portal for leads, resident follow-up and signatures, with synchronization between dashboards and Google Sheets.
A system for managing price quotes, keeping proposal details and producing PDF documents for the sales workflow.
A workflow for processing recordings, managing speaker information and producing editable documents for professional review.
A system for planning field-agent visits and organizing work around customers and visit destinations.
The design includes the normal path and the exception cases: permissions, missing input, an uncertain answer, an external service that does not respond and an orderly hand-off to a person.
Who uses it, who approves, who receives an alert and who holds the source of information.
Valid input, missing input, a wrong permission and a case where the system must stop and ask for help.
The team knows how to operate the system, understand its limits and report a problem in a way that can be fixed.
A process that repeats often, moves between several people or systems, and has a start and a result that can be defined. If the problem is still unclear, start by describing the process rather than building.
Usually not. Often the right piece is a small connection between the CRM, documents, email or WhatsApp and the place where the work is done.
When ordinary rules give a more accurate answer, when there is no reliable information source, or when the cost of a mistake is high and there is no good way to check the result. AI is a possible component, not a requirement.
Yes. When feasibility needs to be checked, the smallest part that can give a real answer is built. A prototype is marked as an experiment and is not presented as a finished system.
Information is reduced, permissions and sources are defined, and tools are chosen according to risk and the organization's policy. Significant actions receive a suitable control point.
The scope of training, documentation, monitoring and maintenance is set in advance according to the system. That part is not left as an unwritten assumption at the end of the project.
The first conversation describes the process, where the information lives and what needs to change. From there it is clear whether to start with training, automation or a system.