The Next Evolution from the Team Behind DeskTrack
Why most Research and Development teams can't show their impact
Research and Development teams are the most expensive part of most tech businesses — and the hardest to measure. You can't tell if a developer is productive or just appearing busy. Rework is invisible until it shows up as a missed deadline. And by the time you identify the bottleneck, the sprint is already over.
Increase in sprint velocity
When developers know their deep work hours are tracked, focus improves immediately
Reduction in rework rate
AI identifies rework patterns and root causes so you can fix the process, not just the symptom
Replaced by TitaPro
Jira, Toggl, Slack, and attendance tracking — all replaced by one integrated system
Faster blocker resolution
Blockers are visible in real time — not discovered in the next standup
Productivity is invisible
You know your team is working. You don't know if they're working on the right things, at the right pace, or with the right quality.
Rework is a silent killer
Your team spends 20-30% of their time fixing things they already built. This rework is invisible in your sprint metrics.
Sprint planning is optimistic
Every sprint is planned optimistically. Every sprint ends with items carried over. The pattern repeats but nobody fixes the root cause.
Deep work is interrupted
Developers switch context 8-12 times per day. Each switch costs 23 minutes of recovery time. Your team is never in flow.
Code review compliance is low
Code reviews are supposed to happen. They often don't. Nobody has data on compliance, and quality suffers as a result.
No visibility into technical debt
Technical debt accumulates silently. By the time it's a problem, it takes 3x longer to fix than it would have earlier.
Every Research and Development workflow gets its own intelligent board.
Sprint Board
Kanban or Scrum board configured for your exact workflow — backlog, in-progress, review, done. No rigid templates.
Developer Activity Board
Deep work hours, context switches, and productive time per developer. Know who's in flow and who's being interrupted.
Rework & Quality Board
Track bugs, rework, and quality issues by developer, sprint, and feature. Identify patterns before they become habits.
Release Pipeline Board
Track every feature from development through QA to production. No release surprises.
Research and Development KPI Scoreboard — Track What Matters
This is what TitaPro looks like
for your Research and
Development team.
These are actual screenshots from TitaPro's Research and Development boards — not mockups, not illustrations. This is what your team will use from day one.
Gantt Dev Board — sprint timeline, milestones, and delivery tracking
Dev OKR Board — engineering objectives, key results, and progress tracking
Developer Details Board — individual activity, deep work hours, and task completion
Developer Timesheet — time allocation by project, sprint, and task type
Everyone sees what they need.
Decisions happen faster.
What your AI Agent tells you every week.
Not raw data. Not charts you have to interpret. Plain-language insights with recommended actions — like having a business analyst on your team 24/7.
"Your team spent 31% of last sprint on rework. 68% of that rework originated from requirements that changed after development started. This is a planning problem, not a people problem. Recommend: implement a pre-sprint requirements freeze protocol."
"Arjun's deep work hours (5.2 hrs/day) are 2x the team average (2.6 hrs/day). His sprint completion rate (94%) is also the highest. His secret: he blocks his calendar from 9am-1pm every day. AI recommends sharing this practice with the team."
"Your code review compliance dropped from 91% to 64% this sprint. This correlates with a 3x increase in production bugs compared to last sprint. Recommend: make code review a hard gate before any PR can be merged."
"We replaced Jira, Toggl, and half our Slack usage with TitaPro. Our sprint velocity improved by 28% in the first month because we finally had visibility into where time was actually going. The rework analysis alone saved us from repeating a process mistake that was costing us 2 sprints per quarter."
See TitaPro for Research and Development in action
Estimating sprint capacity without historical velocity data
Every sprint is planned based on optimism, not data. Teams commit to 40 story points because that's what they think they can do — not because that's what they've historically delivered. The result: every sprint ends with carryover.
TitaPro tracks actual sprint velocity over time and uses it to calibrate future sprint capacity automatically. Your sprint plans become data-driven, not aspirational.
Treating rework as a normal cost of development
Most engineering teams accept that 20-30% of their time goes to rework. They don't track it, don't analyse it, and don't fix the root cause. Rework is the single biggest hidden cost in software development.
TitaPro's rework board tracks every bug, revision, and re-do by developer, sprint, and feature type. The AI identifies the root cause — unclear requirements, rushed code review, or specific developer patterns — so you can fix the process.
Measuring developer productivity by lines of code or hours logged
Lines of code is a terrible productivity metric. Hours logged tells you nothing about output quality. Founders who measure these metrics end up with developers who game them instead of delivering value.
TitaPro measures developer productivity by story points delivered, rework rate, code review compliance, and deep work hours — a composite score that reflects actual output quality.
No code review enforcement
Code reviews are supposed to happen. In practice, they're skipped when deadlines are tight. Nobody tracks compliance. The result: bugs that a 10-minute review would have caught make it to production.
TitaPro's code review compliance board tracks every PR and flags when reviews are being skipped. The AI correlates review compliance with bug escape rates so you can show the team the cost of skipping.
Ignoring context switching as a productivity killer
Your developers are in 4 meetings before noon, responding to Slack messages between tasks, and switching between 3 projects in a single day. Each context switch costs 23 minutes of recovery time. You're paying for 8 hours and getting 3 hours of deep work.
TitaPro's developer activity board tracks deep work hours, context switches, and interruption patterns. The AI recommends schedule changes that protect focus time.
Development Operating System
A connected platform that tracks sprint velocity, developer activity, rework rates, and code review compliance in real time — replacing Jira, Toggl, and manual standup reporting with a single integrated engineering intelligence layer.
Rework Rate
The percentage of development time spent fixing, revising, or rebuilding work that was already completed. A rework rate above 15% indicates systematic problems with requirements clarity, code review, or testing processes.
Code Review Compliance Rate
The percentage of pull requests that received a code review before being merged. Low compliance correlates directly with higher bug escape rates and more production incidents.
Sprint Velocity
The number of story points a team consistently delivers per sprint. Velocity is the only reliable basis for sprint planning. TitaPro tracks velocity over time and uses it to calibrate future sprint commitments automatically.
Deep Work Hours
Uninterrupted, focused work time where a developer is in a state of flow. Research shows that deep work produces 4-5x more output per hour than fragmented work. TitaPro tracks deep work hours per developer using activity data.
Bug Escape Rate
The percentage of bugs that make it to production despite QA processes. A high bug escape rate indicates gaps in testing coverage, code review compliance, or requirements clarity.
Research and Development questions, answered in full
TitaPro tracks developer productivity through outcome metrics — story points delivered, rework rate, code review compliance, and deep work hours — not activity surveillance. Developers see their own scores and can compare them to team averages. Managers see team-level patterns and individual outliers. The goal is to identify systemic problems (like too many meetings or unclear requirements) rather than to monitor individuals. Developers who understand the metrics typically improve their own practices without being told to.
Yes, for most SMB engineering teams. TitaPro includes a full sprint board with backlog management, story point estimation, sprint planning, and Kanban/Scrum views. It adds developer activity tracking, rework analysis, and AI-generated sprint retrospectives that Jira doesn't have. If you have a large engineering organisation with complex custom workflows, you may want to evaluate whether TitaPro's sprint board meets all your requirements before migrating.
TitaPro's AI analyses sprint data across three dimensions: planning accuracy (were estimates realistic?), execution patterns (where did work pile up?), and external factors (were there more interruptions or context switches than usual?). The AI generates a sprint retrospective automatically at the end of each sprint, identifying the primary cause of any delays and recommending specific process changes for the next sprint.
TitaPro's rework and quality board tracks bugs, revisions, and re-dos by feature area and developer. Over time, patterns emerge: certain features have disproportionate bug rates, certain developers have higher rework rates, certain sprint conditions (high pressure, unclear requirements) correlate with more technical debt. The AI surfaces these patterns and recommends targeted interventions — refactoring sprints, training, or process changes — before debt becomes unmanageable.
TitaPro automatically tracks: sprint velocity, on-time delivery percentage, rework rate, deep work hours per developer, code review compliance rate, bug escape rate, estimation accuracy, and developer utilisation rate. All KPIs are calculated from actual activity and sprint data — no manual engineering reporting required.
Ready to give your Research and Development team the system they deserve?
Setup takes under 10 minutes. Your first AI report arrives in 7 days.
