Use-case hub
AI Agent Use Cases
DH79 use-case pages cover practical AI agent workflows such as lead research, warm lead follow-up, CRM updates, proposal drafting, meeting preparation, inbox triage, meeting summaries, SOP writing, internal knowledge search and business monitoring. These are the repeated commercial tasks most suitable for a controlled first AI agent pilot.
Who this is for
- Founders who know they want AI agents but have not chosen a first workflow.
- Sales, operations and marketing teams with repeated drafting or research work.
- Businesses that want measurable first-month value without handing over judgement.
The business problem
The wrong first use case can make AI feel risky, vague or expensive. The right first use case is frequent, useful, measurable and narrow enough to run with human review. 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.
Example workflow
Compare use cases by frequency, value, access needs, approval clarity and risk, then pilot one controlled workflow before adding more agents. 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
- Use-case scorecard and shortlist.
- Agent instructions, examples and success measures.
- Scoped tool connections for the chosen workflow.
- Monitoring, review and expansion plan.
What the AI agents can do
- Research leads and accounts.
- Draft follow-up, proposals and meeting notes.
- Prepare CRM updates, SOPs and internal summaries.
- Monitor competitors, reviews and business signals.
What tools they can connect to
- Gmail, Outlook and shared inboxes
- Google Workspace, Microsoft 365, Notion, Drive and SharePoint
- HubSpot, Pipedrive, Salesforce or lightweight CRM systems
- Slack, Teams, calendars, task tools and internal knowledge bases
- Website CMS, spreadsheets, forms and reporting dashboards where access is scoped
What stays human
- Selecting the first workflow.
- Approving external or sensitive outputs.
- Deciding when quality is good enough to expand.
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
- Score candidate workflows.
- Build one narrow agent.
- Test on real examples.
- Review results and choose the next use case.
Safety and GDPR-aware controls
- Prefer draft-first workflows early.
- Avoid regulated judgement as a first task.
- Keep access limited to what the workflow needs.
- Review outputs before external action.
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 ai agent use cases, DH79 looks for a task where the agent can research leads and accounts, connect only to gmail, outlook and shared inboxes, and leave selecting the first workflow 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 ai agent use cases 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 teams choosing the first workflow for managed ai agents?
It is most suitable when teams choosing the first workflow for managed ai agents 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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