AI Agent

Candidate Outreach AI Agent

Send hyper-personalized recruiting emails at scale

From 'Hey [Name]' templates to deep personalization. 3x higher response rates. Automated sequences that read profiles and write real emails.

Benefits

Personalization That Scales

Generic templates get deleted. Manually researching every candidate takes too long. The Candidate Outreach Agent researches each prospect and writes a unique message referencing their specific background, driving 3x higher replies.

3x

Response rate

90%

Time saved

100%

Personalized

Agentic Flows

Outbound Campaign Workflow

Outreach workflow: candidate research and hook identification, message generation (subject + body), A/B testing of value props, multi-step sequencing, reply detection, and meeting booking.

How it works

Intelligent Message Drafting

The agent reads the candidate's LinkedIn, resume, and public posts, identifies 'hooks' (shared connections, recent projects, school alumni), and drafts a highly relevant message for recruiter review or auto-send.

Self-Learning Agents

The agent improves with every task, adapting to outcomes, applying feedback, and self-correcting using Constitutional AI.

Upto 98% Accuracy

As a result of constant feedback loops, Beam AI Agents refine their approach with every cycle, leading to 98% accuracy across flows.

Smart Model Switching

We call it ModelMesh. Each agent selects the right model for the task, balancing speed, accuracy, and cost in real time.

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Self-Learning Agents

The agent improves with every task, adapting to outcomes, applying feedback, and self-correcting using Constitutional AI.

Upto 98% Accuracy

As a result of constant feedback loops, Beam AI Agents refine their approach with every cycle, leading to 98% accuracy across flows.

Smart Model Switching

We call it ModelMesh. Each agent selects the right model for the task, balancing speed, accuracy, and cost in real time.

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Extract order number, seller information, delivery information, and payment details from the uploaded order forms.

Completed

ID-0E48

Integrations

Connects to Email & LinkedIn

Integrates with Gmail, Outlook, and LinkedIn InMail. Connects to engagement platforms like Gem, Outreach, and Salesloft. Syncs activity to ATS.

Implementation

Better Outreach in 5 Days

Connect your email and define your value propositions. Set personalization rules. Most recruiters see response rates jump significantly in their first agent-assisted campaign.

Step 1

Agent Discovery

Conduct workshop(s) with relevant stakeholders to identify and prioritize use cases and map the requirements

Step 1

Agent Discovery

Conduct workshop(s) with relevant stakeholders to identify and prioritize use cases and map the requirements

Step 2

Agent Setup

Develop and launch your first agent with basic logic and integration (process scoping and recording, test dataset of 30-50 examples, baseline agent running and testing with target output mapping)

Step 2

Agent Setup

Develop and launch your first agent with basic logic and integration (process scoping and recording, test dataset of 30-50 examples, baseline agent running and testing with target output mapping)

Step 3

Agent Training

Test performance and gather feedback from process users (agent optimization up to 80% against expected output, variable-level accuracy measurement and optimization, integrations setup, and feedback API interfacing)

Step 3

Agent Training

Test performance and gather feedback from process users (agent optimization up to 80% against expected output, variable-level accuracy measurement and optimization, integrations setup, and feedback API interfacing)

Step 4

Agent Live

Extend to more workflows and client teams (live and continuous monitoring, human-in-the loop interfacing, node auto-tuning for automated prompt enhancements, >90% accuracy improvement, weekly business logic improvements)

Step 4

Agent Live

Extend to more workflows and client teams (live and continuous monitoring, human-in-the loop interfacing, node auto-tuning for automated prompt enhancements, >90% accuracy improvement, weekly business logic improvements)

Key Features

Smart Writing Tools

Hook Detection

Finds the best reason to reach out: a recent post, a mutual connection, or a specific skill.

Tone Matching

Adjusts formality based on role and industry. Sounds like a peer, not a bot.

Automated Follow-up

Stops when they reply. Nudges gently if they don't. Manages the entire sequence.

Demo

See Outreach in Action

Watch the agent research a Product Manager, notice they just launched a mobile app, and write an email congratulating them on the launch and tying it to your company's mobile initiative.