Agentic AI Framework for Recruiting

About

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Overview

In 2025, HEPIUS supported a recruiting-tech startup aiming to modernize candidate interactions through AI-assisted workflows. The project covered the full journey: early ideation, technical concepting, architecture definition, feasibility studies, MVP shaping, and due-diligence support. The platform focused on structured candidate conversations, transparent reasoning, and scalable workflow orchestration.

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Scope of the Project

• Exploration of AI-driven recruiting workflows
• Agentic system design for structured candidate guidance
• Feasibility checks for matching logic and evaluation flows
• Technical roadmap creation from concept to MVP
• Integration strategy for multi-channel communication (e.g., messaging APIs)

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HEPIUS Responsibilities

• Helping identify USP and core differentiators
• Performing tech evaluations for hyperscaler setup, LLM choices, and API-first design
• Preparing system and architecture documentation for partners and investors
• Implementing early LLM agent workflows for structured data collection
• Coordinating frontend direction and platform UX considerations
• Supporting partner alignment and due-diligence Q&A

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Technology Components

• AWS serverless foundation for scalable backend logic
• API-first system landscape supporting multi-channel inputs
• OpenAI and Anthropic LLMs with agentic orchestration
• Meta messaging API integration for conversational workflows
• Agent-focused abstractions to ensure modular model replacement

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Results

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End-to-End Support

• Provided complete technical leadership across concept, feasibility, architecture, and MVP setup.
• Ensured the platform’s foundation aligned with cost, scale, and compliance expectations.

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Agentic Workflows

• Implemented structured LLM-driven interaction patterns for candidate intake.
• Validated multi-step agent flows such as clarification prompts and structured reasoning.
• Built a blueprint for future matching and scoring logic.

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Multi-Channel UX

• Integrated messaging channels for real-time candidate engagement.
• Enabled a conversational-first experience without dedicated app installation.
• Delivered an accessible, scalable communication model.

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Pilot Outcome

• The startup received a solid technical backbone for continued development.
• Clear documentation supported investor conversations and internal planning.
• The platform now has a robust blueprint for future automation and growth.

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