Leads are handled manually
Managers repeat the same questions, qualify inquiries and copy information into the CRM
We design and launch AI systems that work with CRM, business data and operating rules, with quality controls and a clear outcome. AI assistants, Voice AI, agents, RAG, CRM, 1C/ERP and API integrations are selected around the actual business process
We start with the workflow that consumes employee time, slows down customers or requires constant manual transfer of data between systems
Managers repeat the same questions, qualify inquiries and copy information into the CRM
Routine questions consume team capacity while inquiries outside working hours wait for a response
Website, CRM, ERP, messaging, spreadsheets and documents operate separately, forcing employees to move data manually
The team may use AI tools already, but they are not embedded into the actual workflow or business rules
These are calculated scenarios for typical workflows. They show which metrics are useful before implementation. Actual results depend on source data and the share of operations that can be safely automated
Before: 80 inquiries per day and roughly 5 minutes for first response, clarification and data capture
Solution: AI assistant → qualification → CRM → structured manager handoff
Calculation: 80 × 5 minutes × 22 working days ≈ 147 hours
Before: 25 documents per day and roughly 8 minutes for extraction, classification and data transfer
Solution: extraction → validation → classification → business system
Calculation: 25 × 8 minutes × 22 working days ≈ 73 hours
Before: 40 operations per day and roughly 6 minutes to transfer data between systems
Solution: webhook/API → business-rule validation → system synchronization
Calculation: 40 × 6 minutes × 22 working days = 88 hours
We decide what AI should handle, where conventional automation is enough and where human control must remain
First response, lead qualification, data capture, next-action logic and structured handoff to a manager or CRM
Corporate AI knowledge base, browser voice and text AI, routine inquiry handling and escalation to a person when needed
Documents, reporting, routing, request processing and actions across CRM, ERP/1C, APIs and internal systems
We map the process, data, systems, participants, constraints and acceptance criteria
For a suitable task, we build a first working AI prototype and validate the core hypothesis on a real workflow
We connect CRM, ERP/1C, APIs, websites, documents, knowledge sources and other operating systems
We add permissions, tests, logging, fallback, quality controls, documentation and agreed support
Enter the process parameters. The calculator estimates the cost of manual work and the potential workload represented by the selected automation share. It is not a savings guarantee
potentially automatable manual hours per month
equivalent labor cost per month
equivalent labor cost per year
This is a mathematical estimate, not a forecast or guarantee of actual savings. Real impact is determined after process assessment
The AI24Solutions voice assistant works directly in the browser, supports voice and text interaction and does not require mandatory telephony
Open the assistant on this page and try the flow yourself
Each case shows the business problem, the user flow, and the operational result delivered after launch
A unified system for data, AI generation, review, analytics, and governed workflows
View case → Healthcare · TelegramInquiry qualification, service routing, lead capture, and handoff to administrative staff
View case → AI24Solutions product · SportMethodAI24Solutions productMethodology, annual planning, training sessions, plan versus actual, roles, and analytics in one AI24Solutions product
Explore the product → CRM · automationCustomer management, notifications, roles, integrations, and a controlled production launch
View case →AI automation does not end with the first launch. Processes change, new data becomes available and new automation opportunities appear
We review errors, logs, workflow stability and answer quality
We add actions, data sources, scenarios and integrations
We evaluate new models and tools only where they provide practical value to the process
We help employees use the implemented systems and adapt to workflow changes
Visitors can speak or type directly on the website, get answers from approved company knowledge, and leave a prepared request without a telephony setup
AI helps discover potential customers, prepare managed outreach conversations, qualify interest, and hand off leads that are ready for the next step
Create AI assistants yourself: register, configure knowledge and behavior, and connect a ready-to-use website widget. If you need help, AI24Solutions can configure and implement it for your business
Digital brand representatives kept under team control
A smart ecosystem for nurseries and private plant sellers
A digital system for managing methodology and the training process in a sports school
Practical AI training remains a separate offering for employees and business teams
How to evaluate the use case, business case, security, quality, and pilot outcome before development begins
A practical framework for deciding when a business task genuinely needs AI, and when conventional automation, integration, or process redesign will work better
Read →02A professional AI audit covers the process map, data, business case, risks, architecture options, and pilot selection
Read →03A practical model covering the current process, expected impact, error costs, implementation, operation, and pilot stop criteria
Read →04Choose the first process by measurability, repeatability, data quality, risk, integration complexity, and the ability to validate impact quickly
Read →Show us what employees do manually today, which systems are involved and what outcome you need. After the assessment, we define the first implementation stage and prepare a proposal