Decision Capture & Learning
Every approval, rejection, and edit is recorded as structured data - building the decision history that will power workflow optimization and AI improvement recommendations
Every decision you make is recorded from day one, building the data foundation that will drive continuous workflow improvement.
What It Does
Decision Capture records every action you take across all approval workflows - which option you selected, any form data you submitted, who made the decision, and when. This creates a structured, searchable decision history that spans every workflow and agent in your organization.
Today, that history gives you full auditability: see exactly who approved what, when, and with what information. Coming in Q2 2026, a pattern analysis layer will analyze this accumulated data to surface optimization recommendations - identifying where AI performs reliably enough to remove approval gates, where prompts need refinement, and where workflows can be streamlined.
The key advantage: Decision data starts accumulating from day one of using the platform. By the time pattern analysis launches, you'll already have months of real decisions to analyze rather than starting from zero.
Why It Matters
Traditional automation is static. You set it up once, and it keeps making the same mistakes until someone manually updates it. Your team develops expertise by learning from experience, but your automations don't. This creates a maintenance burden where you're constantly correcting the same issues instead of improving the underlying system.
Decision Capture lays the groundwork for closing this gap. By treating every human decision as structured data rather than a one-time event, the platform builds the foundation that makes data-driven workflow improvement possible. The learning layer being built on top of this foundation will use those accumulated patterns to suggest improvements and optimize workflows over time.
Business Impact
Decision data accumulates passively - no extra work required. Every approval you make, every form you submit, every action you take is captured automatically. When pattern analysis launches in Q2 2026, businesses with 3-6 months of decision history will be able to analyze hundreds or thousands of real decisions rather than starting fresh.
Why this matters: An automation that starts with a 70 percent approval rate and 30 percent requiring edits contains actionable signal. That signal is only useful if it was captured. Businesses that start capturing decisions today will have a head start on the optimization insights that follow.
How It Works
Capture Every Decision
When you take action on an approval task - selecting an action, submitting a form, adding a note - the full decision is recorded: which action you chose, what data you provided, your user ID, and the timestamp. This happens automatically with no extra steps required.
Build Decision History
Each recorded decision joins a structured activity log tied to the specific workflow, agent, and task context. Over time, this creates a complete history of how your team handles every type of approval across your organization.
Coming Q2 2026
The following steps describe planned capabilities being built on top of the decision capture foundation. Steps 1 and 2 above are live today.
Pattern Recognition
The pattern analysis engine will scan decision history to identify trends: high approval rates (AI performing reliably), high rejection rates (AI needs improvement), and consistent edits to the same elements (systematic adjustments needed). Patterns are surfaced only when there is enough data to be statistically meaningful.
Improvement Recommendations
Based on accumulated patterns, the system will suggest specific optimizations: prompt adjustments to fix recurring issues, approval gate removal for workflows where AI has proven reliable, and workflow refinements based on how your team actually uses each process.
Continuous Improvement
As you implement recommendations and continue making decisions, the learning cycle compounds. Automations become progressively more aligned with how your business actually operates, and the approval workload for your team decreases as AI reliability improves.
Use Cases
Common Questions
What decision data is captured today?
Every action taken on an approval task is recorded: the action selected (e.g., "Approve", "Request Revision"), any form data submitted with that action, the user ID of the person who made the decision, and the timestamp. This data is stored in the activity log and linked to the specific workflow and task context.
When will pattern analysis and recommendations be available?
Pattern recognition and optimization recommendations are planned for Q2 2026. The decision capture infrastructure being built now is specifically designed to support this capability. The more decisions captured before launch, the richer the analysis will be when it goes live.
Will the system change my workflows automatically?
No. When recommendations launch, the system will surface insights and suggest specific changes - you decide whether to implement them. The platform never modifies workflows autonomously. You maintain full control over when and how improvements are applied.
Can I see my decision history now?
Yes. The activity log provides a full record of all approval decisions across your organization: who took which action, when, and on which task. This is available today for audit and review purposes, independent of the pattern analysis features coming in Q2 2026.
What if my preferences change over time?
When pattern analysis launches, the system will weight recent decisions more heavily than older ones. If your team shifts preferences - for example, adopting a new email tone standard - new patterns will emerge and displace older ones in the analysis. You will also be able to manually reset learning for specific workflows when making intentional strategic changes.
Last Updated: 2026-03-21