Discovery call summaries
Start with the source records and define the information a reviewer needs before this step can proceed.
Automation runs through the software, inboxes and documents your team already uses. Stop being the bottleneck on proposals, discovery summaries and weekly client reports. Built for owner-led consultancies and professional firms under 15 staff who'd rather get half a day per client per week back than hire a delivery manager to write the same updates.
Discovery call summaries, built inside the software your team already uses, with people approving what matters.
Teams is where your staff instruct the AI. This dashboard is the management layer: live workflows, queued work, exceptions and approvals for professional services firms.
The dashboard is the window in. Underneath it, specialist AI agents handle inbox triage, crm update, client follow-up inside the software professional services firms already use.
Every Horizon solution includesThis is the professional services product. It uses the same live-agent pattern as every Horizon build, shaped around the workflows and software already in use.
Open the live dashboardProfessional services firms use AI automation to cut repeated admin - discovery call summaries, proposal drafts - while keeping a person on anything that touches a client, payment or compliance record. Horizon AI builds one workflow at a time inside the Microsoft 365, Google Workspace, HubSpot tools you already run, with the scope, access requirements and testing agreed before implementation.
Stop being the bottleneck on proposals, discovery summaries and weekly client reports. Built for owner-led consultancies and professional firms under 15 staff who'd rather get half a day per client per week back than hire a delivery manager to write the same updates.
The first build sits inside familiar systems - inboxes, documents, client portals, practice platforms, booking tools and reporting workflows professional services firms already rely on every day.
Start with the source records and define the information a reviewer needs before this step can proceed.
Prepare the routine work for the responsible person, with the original context available for checking.
Agree the system handoff and how the team handles missing information or conflicting records.
Use clear trigger and completion rules so repeated or failed work stays visible to its owner.
Keep draft outputs separate from approved actions and define when the workflow should ask for help.
Test representative examples and exceptions before deciding how much of this work should be automated.
Review the current process, software stack, data access points and manual handoffs.
Choose the first workflow, approval gates, implementation path, timeline and quote.
Build, test and launch the workflow inside approved business systems with human review.
Turn the first useful workflow into a practical AI roadmap across the business.
The integration path depends on permissions, API access, subscription tier and security rules.
A free 30-minute conversation with our Director about the work, the systems involved and what needs a closer look. Detailed assessment and implementation are quoted separately.