Stop estimating what your engineering organization is worth.
CRED gives technology leaders a real-time view of what engineering is producing, where capacity is concentrated, and which delivery risks are compounding before they reach the board.
A. Chen
Senior SWE
94
$412/hr
Top
M. Torres
Staff SWE
91
$389/hr
Top
R. Patel
SWE II
88
$341/hr
Healthy
S. Kim
Senior SWE
72
$287/hr
Watch
J. Okafor
SWE II
61
$241/hr
Risk
Active risk signals
Payment service p99 latency spike
2 engineers hold 67% of critical path
Sprint velocity down 22% over four weeks
Engineering is the most expensive function. It is also the least measured.
CTOs make resourcing decisions, roadmap commitments, and hiring calls from sprint proxies and capacity estimates that are already stale by the time they reach the planning room.
The signals that predict engineering output already exist across GitHub, Jira, Slack, CI, and product systems: contribution velocity, technical debt accumulation, domain concentration, and dollar-value-per-hour output. The problem is that they are not connected into a leadership-grade system.
Software developers spend only 32% of their time writing code. The remaining 68% is consumed by meetings, context-switching, reviews, and coordination overhead.
McKinsey & Company, 2023
The average developer spends 17.3 hours per week dealing with maintenance issues and technical debt, more than 40% of the working week.
Stripe, The Developer Coefficient, 2018
Signal timeline
The gap between visibility and cost.
Dollar value efficiency decline
Cost-per-output rising 18%; cross-team pattern confirmed.
Capacity concentration
67% of critical-path output concentrated in two contributors.
Velocity divergence
Three engineers below benchmark for six consecutive sprints.
Missed roadmap commitment
Board visibility, customer impact, and revenue consequence.
Closing the output black box.
CRED connects the systems already recording engineering activity and translates them into leadership-grade output, capacity, risk, and capability intelligence.
Six active signals across productivity, capacity, debt, and capability dimensions, derived from GitHub, Jira, Slack, CI, and product data.
Productivity intelligence
Individual and team output scored against objective internal benchmarks.
Capacity visibility
Utilization aligned to roadmap priorities, squads, and critical paths.
Dollar value output
Engineering hours mapped to business return and project impact.
Technical risk monitoring
Debt, fragility, and delivery failure signals surfaced before they block execution.
Capability mapping
Contribution depth by domain, derived from actual work output.
Five engineering intelligence models inside one operating system.
Each model follows the same cadence: connect the source systems, score the signal, surface the risk, and turn it into an action the leadership team can defend.
Engineering Productivity Intelligence
What your engineers are producing, not just what they are doing.
CRED connects GitHub, Jira, Slack, and product data to build a true picture of contribution, velocity, quality, collaboration depth, and cross-system impact.
Individual velocity trends against role-specific benchmarks.
Review turnaround, rework rate, and defect origin patterns.
Cross-team contribution and siloed output risk.
Sprint-over-sprint drift before it becomes delivery risk.
A. Chen
$412/hr
94 vel
M. Torres
$389/hr
91 vel
R. Patel
$341/hr
88 vel
S. Kim
$287/hr
72 vel
An intelligence engine that gets harder to replicate every quarter.
Every productivity signal sharpens the next hiring benchmark. Every capability gap improves the next resourcing call. Every output calculation feeds the model so the next quarter starts clearer than the last one ended.
Connect
GitHub, Jira, Slack unified in days
Score
Every engineer and team benchmarked
Surface
Signals delivered before they become costs
Compound
The intelligence model sharpens every quarter
Engineering Intelligence Score
94/100
Model confidence improves as more system signals, outcomes, and resourcing decisions flow through CRED.
$/hr output baseline established across 100% of engineers
Predictive output accuracy reaches 87%
Engineering Intelligence Score improves 28 points
Built for enterprise engineering environments.
Engineering intelligence must be trusted by employees, HR, legal, and leadership. CRED is designed as a private, audited coaching and development layer.
All engineering intelligence is processed within your private instance. Individual contributor data, commit history, output scores, and capability assessments are never shared, pooled, or used to train models outside your organization.
Every access event is audited and exportable. Role-based access ensures engineers see their own performance and coaching, managers see their direct reports, and leadership sees organizational aggregates.
SOC 2
Independently audited security controls.
Full audit trails
Every access event logged and exportable.
Role-based access
Engineers see their data. Managers see their teams.
Private instance
Your data never leaves your environment.
The signals that define your next two quarters are already in your systems.
The question is whether anyone is reading them before a missed commitment, a surprise resignation, or a board conversation you were not prepared for.
Product walkthrough
Schedule your engineering audit
See your engineering stack scored live across output, capacity, and risk signals.
Schedule your engineering auditExecutive briefing
Request an engineering briefing
Spend 45 minutes with platform architects around your organization and operating context.
Request an engineering briefing