Delivery Intelligence from Jira historyStop Re-Solving
Already-Solved Problems
Before teams write a single line of code, they spend real time rediscovering answers that already exist in Jira. Recall brings relevant historical context to the surface.
Industry Benchmarks
Based on peer-reviewed studies and large-scale industry surveys
Industry-wide benchmarks shown for context. Actual impact varies by organization.
Recall focuses specifically on reducing duplicate discovery and rework caused by rediscovering already-resolved Jira issues.
The Problem
Jira stores years of history, but teams still:
Discover duplicates only after analysis has already begun
Re-create bugs that were already fixed
Re-investigate problems with existing answers
Lose context as teams change or scale
Depend on memory, labels, or manual search
The result is unnecessary work and reduced delivery predictability.
Jira remembers everything —
but it doesn't learn from it.
Intelligence Layer for Jira
Recall adds a lightweight intelligence layer on top of Jira Cloud. It continuously learns from resolved issues and surfaces relevant historical context.
No workflow changes. No process enforcement.
How Recall Works
Seamless integration that requires zero process changes
Conceptual overview — validated with early users. Details may evolve.
Learn from Resolved Issues
Recall continuously learns from resolved issue titles, descriptions, and resolution notes.
Instant Match Suggestions
When a new issue is created, Recall proactively surfaces similar resolved issues.
Context That Matters
Teams see examples of how similar problems were handled in the past.
Less Redundant Work
Historical context is available before engineering time is spent.
Benefits for Engineering Organizations
Measurable improvements backed by research
Reduce Wasted Effort
Prevent duplicate investigations and re-solving of known problems, directly reducing engineering waste.
Improve Delivery Predictability
Fewer surprises from rediscovered issues means more consistent sprint outcomes and release timelines.
Maintain Quality at Scale
Surface relevant historical context before engineering time is spent, catching issues earlier in the cycle.
Preserve Institutional Knowledge
Make historical resolutions accessible even as teams evolve, grow, and change.
Who Benefits Most
Recall is designed for organizations where Jira knowledge spans teams, products, and time
Engineering Leadership
- CTOs and VPs of Engineering seeking delivery efficiency
- Directors and EMs managing multiple teams or products
Product & Quality
- Product managers responsible for backlog hygiene
- Quality leads tracking recurring issues and regressions
Support & Service Desk
- Support teams creating Jira issues without historical context
- Service desk teams triaging incoming requests
Best fit: Mid-size to large Jira Cloud instances where institutional memory matters.
What Recall Is Not
To set clear expectations
Does not replace human decision-making
Does not enforce estimates or planning commitments
Does not predict delivery dates
Recall simply ensures teams don't rediscover what they already know.
Interested in solving this problem?
We're validating Recall with a small number of engineering-led teams. If this resonates, request early access and we'll reach out to learn about your context.
Request Early Access
We're validating Recall with a small number of engineering-led teams.