Put AI to work on the tasks that slow your team down. We design and build agents that use your business information, work with your tools, and follow the rules you set.
Custom AI work
Data hygiene & enrichment
Clean up CRM data and fill in missing business information. This agent brings data hygiene and enrichment together to make customer records more useful to the people working with them.
Enrichment toolsApollo · LinkedIn · SERPER · BrowserBase
Discuss your CRM dataAccounting document handling
An accounting agent for secure invoice scanning and purchase order and sales order handling. Built with Amazon Bedrock and AgentCore around the documents that move through an accounting workflow.
Built withAmazon Bedrock · Amazon Bedrock AgentCore
Discuss your accounting workflowSales research & CRM opportunities
Identify and qualify sales opportunities, then create those opportunities inside the CRM. This agent connects business development research to a customer record your sales team can work with.
Example workflow
An example of an agent helping a service team prepare and route a request.
Use the details from an approved form, inbox, or business system.
Find relevant customer information in the connected records.
Summarize the request and suggest the next action for review.
Create or update the record and assign the agreed next step.
If the information is incomplete or an action needs approval, the agent can flag the request for a person. We define that route before the workflow goes live.
Choose the documents, records, and business context the agent needs. Keep access appropriate to the work.
Decide which systems it can use, what it can change, and which actions require a person’s approval.
Plan for missing information, uncertain results, and failed connections, with an owner and a next step.
We use Amazon Bedrock and Amazon Bedrock AgentCore as part of our approach to building custom agents on AWS.
How we build on AWSEach project starts with a defined workflow and an agreed way to judge whether it is useful. The scope can include:
Start with one defined workflow. We review your systems, build a focused version, and test it with the people who know the work. Before launch, we agree on support, running costs, and who handles changes.
See how we build your agentA chatbot usually answers within a conversation. An agent can also use connected tools to carry out steps in a workflow, such as finding a record, preparing a response, or creating a task. We define which actions are allowed and which need approval.
Start with a recurring task your team can describe clearly. We look at the information it needs, the tools it touches, the exceptions, and the value of improving it. Sometimes a simpler automation is the right fit; discovery helps make that decision.
We start with the systems you already use. Integration options depend on their APIs, access controls, and the condition of the data. We identify those constraints before agreeing the build.
We define what the agent can access, which actions it may take, and where a person must approve the next step. The implementation can include activity records, exception routing, and a way to pause the workflow. We agree and test those controls as part of the project.
We agree who will review activity, maintain the connected information, and handle changes or issues. Documentation, handover, and any ongoing support are defined in the scope, so your team knows how to operate the workflow.
Tell us what starts the work, which tools are involved, and what a good result looks like. We’ll help you find a practical place to begin.
Discuss your project