Example implementation
Example: AI Follow-Up Agent for a Recruitment Firm
Example: AI Follow-Up Agent for a Recruitment Firm is most useful when recruitment firms need repeatable work handled consistently without losing human control. DH79 maps the workflow, builds private AI agents, connects the right tools, sets approval gates and runs the system as a managed service. The starting point is not a generic AI demo. It is a narrow operational workflow such as research, follow-up, content, meeting preparation, CRM updates, admin or monitoring, launched carefully and improved each month.
Who this is for
- recruitment firms considering a practical first AI agent workflow.
- Buyers who want an example implementation, not a claimed case study.
- Teams that want to see what stays human before booking a call.
The business problem
Recruitment consultants lose momentum when client and candidate follow-up depends on manual notes and memory. This is an illustrative example, not a client case study or performance claim. The important test is whether the work is frequent enough, valuable enough and controlled enough for an agent to help without hiding risk. DH79 starts with a narrow workflow because useful agents need clear inputs, clear outputs and a named human owner.
The agent workflow
The agent reviews call notes, candidate status and CRM context, drafts follow-up messages and creates reminders for consultant approval. The workflow is designed so the agent prepares, drafts, summarises or monitors, while a human remains responsible for approval where judgement, reputation, compliance or customer trust is involved.
What DH79 sets up
- Workflow map, access rules and success measures.
- Agent workspace with approved examples and operating instructions.
- Tool connections needed for the example workflow.
- Draft-only pilot, logs and review before expansion.
What the AI agents can do
- Draft client follow-up
- Summarise candidate status
- Create reminders
- Flag missing information
What tools they can connect to
- Recruitment CRM or ATS
- email and calendar
- call notes
- candidate documents
What stays human
- Candidate suitability
- client relationship judgement
- final messages
DH79 deliberately avoids promising fully autonomous business judgement. The safest commercial gains usually come from agents preparing the work, making gaps visible and giving humans better drafts, summaries and reminders.
First 30 days
- Map the workflow and source material.
- Build the first agent and review outputs manually.
- Test on real examples with no autonomous external action.
- Measure usefulness and decide whether to expand.
Safety and GDPR-aware controls
- This example keeps sensitive actions human approved.
- No client, candidate, patient or customer claims are invented.
- Access stays scoped to the workflow.
- Success is measured from real usage, not assumed in advance.
How success would be measured
- Faster follow-up after calls
- fewer stale opportunities
- cleaner CRM notes
- consultants spending more time on relationships
Pricing and scope
DH79's managed package starts from £5,000/month inside an agreed operating scope. Work that needs unusual volume, specialist integrations or regulated review is scoped before launch so costs and responsibilities are clear.
How to judge whether this should be your first agent
A good first agent is not the most exciting idea in the business. It is the workflow with clear inputs, repeatable steps, visible mistakes and a human owner who can approve the output. For example: ai follow-up agent for a recruitment firm, DH79 looks for a task where the agent can draft client follow-up, connect only to recruitment crm or ats, and leave candidate suitability with a person. That makes the pilot easier to measure and safer to improve.
- Bring two or three real examples of the current workflow, including a strong example and a messy edge case.
- Decide who owns approval, who receives the draft or summary, and what would count as a useful first-month result.
- Start with a draft, research, preparation, triage or monitoring task before allowing any agent to take external action.
FAQs
Can DH79 set up example: ai follow-up agent for a recruitment firm without our team managing prompts?
Yes. DH79 maps the workflow, builds the agent instructions and private workspace, connects the agreed tools, sets approval rules, monitors usage and improves the system. Your team should understand the operating rules, but it should not have to manage tokens, hosting or prompt maintenance.
What should stay under human approval?
External messages, legal or financial commitments, sensitive client communication, medical or regulated judgement, unusual edge cases and anything that could affect reputation should remain human reviewed unless a narrower approval policy is agreed.
How quickly can the first workflow go live?
A narrow first workflow is normally designed during the first month. The first 30 days focus on workflow audit, data and tool access, agent build, controlled testing, team feedback and a decision on what to improve or add next.
How does DH79 reduce risk?
DH79 uses scoped permissions, least-privilege access, human approval gates, logs, draft-only modes for sensitive work, clear escalation rules and monthly review. The aim is useful operational leverage without handing important judgement to an unsupervised system.
Is this suitable for recruitment firms?
It is most suitable when recruitment firms have repeatable research, drafting, preparation, follow-up, admin or monitoring work and want a managed service rather than a DIY platform. If the first use case is too vague, DH79 starts by narrowing it into a controlled pilot.
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