Buyer intent
AI Agent Pilot to Production
AI Agent Pilot to Production is most useful when businesses that need to move from ai pilot to live operations 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
- Teams with a promising AI experiment that is not yet dependable.
- Businesses that need testing, permissions, monitoring and adoption before rollout.
- Founders who want a safe path from one workflow to a managed agent team.
The business problem
Most AI pilots break when they meet real operations. The data is messier, edge cases appear, staff need training, permissions are unclear and nobody knows who fixes weak outputs. Production means ownership, not just a clever prototype. 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
A pilot-to-production path might take a meeting summary agent from manual uploads to a controlled workflow that reads approved transcripts, drafts actions, updates a task board and sends a human-reviewed summary. 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
- Pilot review and risk assessment.
- Production workflow design with logging, approval and fallback rules.
- Tool connections and access scoping.
- Monitoring cadence and monthly improvement backlog.
What the AI agents can do
- Harden prompts, instructions and source data.
- Create test examples and expected output patterns.
- Define review, escalation and rollback rules.
- Train the team on when to use the workflow.
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
- Go/no-go decisions, edge-case judgement and approvals.
- Review of sensitive records and external communication.
- Ownership of business policy and risk appetite.
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
- Audit the existing pilot and failure modes.
- Rebuild the workflow around controlled inputs and outputs.
- Run side-by-side tests with human review.
- Launch only the reliable part and track exceptions.
Safety and GDPR-aware controls
- Production access is narrower than prototype access.
- Logs and test cases are required before rollout.
- Human approval remains for sensitive actions.
- The system is improved from observed errors, not assumptions.
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 pilot to production, DH79 looks for a task where the agent can harden prompts, instructions and source data, connect only to gmail, outlook and shared inboxes, and leave go/no-go decisions, edge-case judgement and approvals 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 pilot to production 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 businesses that need to move from ai pilot to live operations?
It is most suitable when businesses that need to move from ai pilot to live operations 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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