MerkleBuild an
AI-native business.
We transform your company by building custom AI agents that drive outcomes
AI agents at work in your industry.
Example workflows, tailored to your systems and reviewed by your team.
How we build for your business.
We work with your team to choose one workflow worth improving, based on the time, cost, or revenue at stake. We establish a baseline and check the data, systems, and integration options before agreeing the scope. If an existing tool can meet the need, or the business case is weak, we say so before building.
We build agents that carry out the work across your existing systems. Your team helps define what they can access, which decisions need approval, and when to hand work back to a person. We test together before launch.
We monitor the workflow, review errors and operating costs, and measure results against the starting point. We help your team use the solution and update it as your systems and processes change. Support responsibilities and the scope of ongoing maintenance are agreed up front. We expand only when the results support it.
Built with your MSP.
Keep the controls you need.
We work with your managed service provider to connect agents to the tools your team already uses. Your MSP knows your systems and security requirements. We build and maintain the agents, with clear responsibilities for access, support, and changes.
Control data access
Agree which systems and information the solution can use, who can access it, and how data is handled by the selected tools.
Set approval boundaries
Decide what AI can prepare, what requires a person’s approval, and what happens when a request falls outside the agreed scope.
Know who owns support
Define who monitors the solution, handles issues, and approves changes. Your team and your MSP have a clear point of contact.
Before we start.
What does an AI-native business actually look like?+
Agents are part of how work moves through the business: they use approved information, update systems, complete defined tasks, and hand decisions to the right people. Your team manages outcomes and exceptions rather than manually coordinating every step. We build toward that in stages, around a business case.
We already use ChatGPT or Copilot. Where does Merkle fit?+
Those tools may already cover individual tasks such as drafting or summarising. Merkle helps when a workflow needs to connect information, approvals, and actions across your business systems, with someone responsible for keeping it working.
We first assess what your existing tools can do. Custom development should have a clear business case, rather than add another tool for your team to manage.
How will we know whether it’s worth doing?+
We agree on the business outcome first: more client capacity, a shorter delivery cycle, fewer unfilled appointments, or faster billing. We compare the current baseline with the cost of building, operating, and reviewing the workflow. If the case is weak, we change the scope before building.
How does pricing work?+
Pricing is custom, based on the outcome you want to achieve, the workflow complexity, and the integrations needed.
After discovery, we outline the scope and expected value, separating implementation costs, ongoing support, and any model or platform usage fees. We explain what drives variable costs and agree how usage will be tracked and reviewed, so you can assess the full cost before the build begins.
Will we have to replace our existing software?+
We start with the tools you already use, including older systems. During discovery, we check available integrations, data quality, and permissions. Some tools have limited connections or require exports and manual steps. We explain those constraints, any additional tools needed, and the maintenance involved before agreeing the build.
How will our confidential information be handled?+
Before implementation, we agree which data the workflow needs, who can access it, and which actions require approval. With your team and MSP, we review the selected providers’ data-handling arrangements, including retention and model-training settings, against your requirements.
Sensitive workflows may need tighter access boundaries or a different deployment approach. We confirm what is feasible and document the agreed controls before connecting your data.
What happens when AI gets something wrong?+
Agents operate within agreed permissions and approval gates. We test failure cases, route exceptions to your team, and keep a record of actions for review. Decisions that require professional judgment stay with the responsible person. Reported errors feed into ongoing improvements.
What should AI do
for your business?
Bring us a bottleneck or a business goal. We’ll explore where
custom agents could help and what success would look like.