Document preparation
Collect information from a transaction, identify missing details, and prepare a draft for a person to review. Agree on required fields and approval rules before an agent can move work forward.
AI agent development
AI agents, custom built for your business.
Ida designs, builds, and supports AI agents for business workflows. We start with the work your team does every day, connect the systems it depends on, and build an agent around the decisions and handoffs that matter.
When this is a good fit
A custom agent makes sense when a process needs to interpret documents, gather context from several systems, and decide what should happen next. The best starting point is a recurring workflow with clear inputs, a defined outcome, and a person who can review exceptions.
Workflows to explore
These are starting points for discovery. The implementation depends on your systems, data, and approval requirements.
Account research and meeting support
Bring account context and relevant documentation into one workspace. Internal Deal Assistant shows this approach in practice for technical sales, with live meeting context and cited answers.
Operational coordination
Gather requests, check the information needed to act, and route the next step to the right person or system. Escalate ambiguous requests instead of guessing.
How we approach the first deployment
We map the workflow, identify available data and integrations, and define what the agent may do. The first deployment focuses on one process. We evaluate its output, review exceptions with your team, and refine it before expanding its responsibilities.
What success should look like
Measure completion rate, reviewer corrections, time spent per task, and unresolved exceptions against the current process. A useful agent should reduce the work around a task as well as the time it takes to produce an answer.
Questions before you start
How is an AI agent different from a chatbot?
A chatbot primarily responds to messages. A workflow agent can gather information, use tools, and move a task through several steps. We define its permissions and approval points around the specific process.
Can an agent use our existing systems?
We assess the tools, data, and access your workflow needs during discovery. Integration options depend on each system's APIs and permissions. You do not need to replace your whole software stack to start.
How much does custom AI agent development cost?
Scope depends on integrations, data quality, workflow complexity, and review requirements. Share one process and the systems involved so we can discuss a focused first deployment and what it would take to build.