Agentic Implementation
Most organizations have seen an AI demo. Far fewer have an agent doing real work on a Tuesday morning. We close that gap: we pick one workflow that matters, put agents on it, and stay until it runs in production.
What we do
- Agents that read, sort and act on inboxes, documents and tickets
- Synthetic colleagues with their own accounts, working inside your team chat and task board
- Pipelines that run on relationships, from fundraising to sales and partnerships
- Approval steps built in: a person signs off on anything that moves money, carries a signature or ships to customers
- Fixed budgets and audit logs, so every action can be traced and every cost is known in advance
How we work
01Scope
We pick one workflow with a clear owner, a measurable outcome and real volume. Not a pilot for its own sake.
02Build
Agents go into the tools your team already uses: email, chat, the task board, the files. No new platform to learn.
03Measure
We track what the agent did, what a person corrected and what it cost, from the first week.
04Hand over
Your team owns it, with the runbook, the guardrails and the knowledge of where it breaks.
Related work
Back Office
Agentic Implementation · Admin & FinanceThe administration and finance of a group of companies, handed to agents.
Synthetic Colleague
Agentic Implementation · EngineeringA synthetic developer, onboarded into a product team like any new hire.
Raise Engine
Agentic Implementation · FundraisingA startup's funding round, run as a system instead of a spreadsheet.
Questions
What is agentic AI implementation?
It is the work of putting AI agents into a real business process so they take actions, not just answer questions: sorting mail, drafting documents, preparing payments, writing code. Implementation covers the scoping, the integration into existing tools, the guardrails and the handover.
How do you keep an AI agent from making costly mistakes?
Every agent we deploy has explicit approval steps. A person approves anything that moves money, carries a signature or reaches a customer, and an agent can never approve its own work. Agents also run inside fixed budgets and keep a log of every action.
Do we need a new platform?
No. We build agents into the systems your team already works in, such as email, chat, task boards and shared drives, so adoption does not depend on people learning a new tool.
Do you use these agents yourselves?
Yes. The back office of our own group of companies runs on the same approach every day, which is how we learn where agents break and how to fix them before a client hits the same problem.
Insights
Human approval for AI-prepared payments: a practical setup
2026-10-22When an AI agent prepares payments, one person should approve each batch, a different person should control vendor details, and every step should be logged. Here is how to set it up.
AI agent, chatbot or automation: which does your process need?
2026-10-15Automation suits fixed steps, a chatbot suits answering people, and an agent suits messy inputs where the next step depends on what it reads. Most processes need a mix of all three.
Why our AI agents never move money on their own
2026-10-15Every agent we deploy can draft, sort and prepare, but a person approves anything that moves money, carries a signature or reaches a customer. Here is how that rule works in practice and why it makes agents faster to adopt, not slower.
Have a workflow in mind?
Tell us what takes too much of your team's time.
info@newkinco.com