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AI Platform for Precision Sales Hiring

A tool for sourcing, evaluating, and hiring sales candidates with AI matching, analytics, and a Telegram interface

Industry:
HRTech / B2B SaaS
Timeline:
6 months
Type:
Telegram Mini AppWeb Platform
Platform:
Telegram / Web / AI Module

[client]

/01

The head of sales at a major consulting firm approached us to improve hiring accuracy.

Existing tools did not provide a structured process.

The project goal was to build a platform where hiring follows funnel principles: with filters, analytics, stage management, and priorities.

The main focus was on matching the candidate profile to the business need.

[our responsibility]

/02
Designing the hiring model: roles, stages, evaluations, AI hints
Mini App and web interface design for HR
Mini App and web platform development
Backend and AI matching module
Integration with Telegram, analytics, and notification system

[key users]

/03

Candidate in Telegram

Finds vacancies, applies, and receives feedback.

HR Manager

Posts vacancies, analyzes responses, and communicates with candidates.

Head of Sales

Joins at the final stage, analyzes the shortlist, and uses analytics for decision-making.

[about the product]

/04
Focus on Relevance

Candidates pass through filters and a match score. Only suitable profiles are shown to the employer.

Mini App for Candidates, Web for HR

In the Mini App users find vacancies, apply, and receive notifications. The web interface gives HR access to responses, analytics, and communication.

Smart AI Layer

The system generates vacancies from a brief, auto-fills candidate profiles from resumes, and evaluates the degree of match. It flags potential inconsistencies in experience, motivation, and expectations.

[the client had]

/05
Understanding of key hiring problems and a need for automation
A request for AI matching and a fast path to MVP
Smart Hire recruitment platform

[team]

/06
1 Product Manager
2 UX/UI Designer
3 Backend Engineer
4 Frontend Engineer
5 AI Engineer
6 QA Specialist

[key features]

/07

Match Score

Candidate match score across key parameters: skills, experience, expectations, region

Automatic Job Descriptions

Generation of structure and text based on inputs: role, level, work format

Resume Data Extraction

Automatic candidate profile population based on PDF analysis

Reviews & Applications System

Built-in feedback tools for employers and candidates

Recommendation Engine

Matching relevant vacancies for candidates based on their profile and behavior

AI Vacancy Filtering

Filtering out uninformative, duplicate, or irrelevant postings

[development stages]

/08
1 Internal process audit
2 Customer journey and interaction scenario analysis
3 AI assistant and chatbot funnel design
4 Interface prototyping: CRM, Telegram, Mini App
5 Core module development: AI, scenarios, admin panel
[tech stack]
/09
React
React
Next.js
Next.js
TypeScript
TypeScript
WebSocket
WebSocket
OpenAI API
OpenAI API
Python
Python
FastAPI
FastAPI
PostgreSQL
PostgreSQL
Redis
Redis
Docker
Docker

[technical challenges & solutions]

/10
01
Challenge

Implement three-level permissions (role, department, entity type)

Solution

Custom ACL module with caching and flexible configuration

02
Challenge

Improve relevance of AI suggestions and reactions

Solution

Intermediate layer with enriched context — routes, roles, statuses, task parameters

03
Challenge

Avoid stuck tasks and implicit blockers

Solution

AI generates text comments explaining reasons and suggests actions (e.g., "To proceed, you need to...")

[results]

/11
  • relevant responses within the first 24 hours
    60 %
  • users complete the Telegram Mini App funnel
    > 75 %
  • time to close a position reduced
    35 %
  • Match Score system applied to every response

    Confirmed by post-implementation research

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