Portfolio monitoring
One technical baseline across every portfolio company.
Make technology a measurable part of every value creation plan, from the first 100 days to exit.
Portfolio technology baseline
Q2 2026 · five portfolio companies| Metric | Company A | Company B | Company C | Company D | Company E |
|---|---|---|---|---|---|
| Code health0 to 100 | 78 | 66 | 58 | 42 | 72 |
| Key person dependencytop owner share, largest critical system | 14% | 41% | 26% | 38% | 9% |
| Innovation vs maintenanceinnovation share of engineering effort | 64% | 48% | 55% | 22% | 58% |
| Vulnerabilitiescritical / high | 0 / 2 | 1 / 9 | 6 / 31 | 9 / 47 | 0 / 4 |
| Scalability tierT1 most scalable, T5 least | T2 | T2 | T3 | T4 | T2 |
| Delivery (DORA) | |||||
| Deployment frequencydeploys per week | 11.5 | 4.2 | 9.8 | 0.2 | 0.6 |
| Lead time for changeshours | 9.5 | 23.6 | 14 | 910 | 210 |
| AI adoption in development | |||||
| AI-written codeshare reaching production | 38% | 26% | 44% | 3% | 17% |
| AI code merged unreviewedshare of AI-written lines | 4% | 6% | 58% | n/a | 11% |
| Security and supply chain | |||||
| Outdated dependenciesshare more than two major versions behind | 6% | 11% | 18% | 34% | 8% |
| Licence riskcopyleft or unknown licences | 0 | 2 | 1 | 5 | 0 |
Technology value creation
Four questions every value creation plan asks of technology.
Each one is measured the same way in every portfolio company, every quarter.
Growth
Can the platform carry the growth plan?
See each company's scalability tier, based on the architecture and deployment setup in its code. Know which platforms need investment first.
Measured by
- Scalability tier
- Architecture
Speed
Which teams ship fast and securely?
Compare deployment frequency and lead time for changes across companies. See how much AI-written code is merged without review.
Measured by
- Deployment frequency
- Lead time for changes
- AI code merged unreviewed
Cost
How much engineering time goes to maintenance?
See the split between maintenance and new features in every company. Know where technical debt takes the most engineering time.
Measured by
- Innovation vs maintenance
- Technical debt
Risk
What would a buyer's diligence find?
See open vulnerabilities and key-person risk in every company. Fix them before the exit process starts.
Measured by
- Vulnerabilities
- Key person dependency
How CodeDD supports value creation
From manual reporting to live evidence.
Much of tech reporting today still runs on questionnaires, calls and spreadsheets. CodeDD automates evidence collection and interpretation straight from the code and the CI/CD pipeline.
Before CodeDD
With CodeDD
Questionnaires and interviews. Every review starts with long forms and management calls. Portfolio teams lose days to it.
Answers from the code. CodeDD reads each company's Git history directly. Interviews focus only on findings that need context.
Inconsistent data. Each portco reports its own way. Nothing lines up, so no one can compare.
One scorecard for all. Same definitions and same time window for every company. You compare like with like.
Data that arrives late. Numbers come in weeks after the quarter closes. Problems have already grown.
Data that stays current. Git syncs daily, so a slipping company shows up weeks before the board meeting.
Progress you have to take on trust. Status updates say every plan is on track. No one can verify it.
Progress you can prove. Every company's change since the last audit is measured, so you can show it to buyers at exit.
Trusted by
Delivery (DORA)
Which portfolio companies can deliver their plan?
The four key DORA metrics for every company, on the same definitions and the same 90-day window. Company C deploys almost as often as Company A, but one release in four needs a fix, so its speed is costing it stability.
Portfolio delivery (DORA)
Last 90 days · five portfolio companies| Metric | Company A | Company B | Company C | Company D | Company E |
|---|---|---|---|---|---|
| Throughput | |||||
| Deployment frequencydeploys per week | 11.5 | 4.2 | 9.8 | 0.2 | 0.6 |
| Lead time for changeshours | 9.5 | 23.6 | 14 | 910 | 210 |
| Failed deployment recoveryhours | 0.8 | 3.5 | 31 | 190 | 20 |
| Instability | |||||
| Change fail rateshare of deploys needing a fix | 3.1% | 8.2% | 27% | 12% | 6.5% |
AI in development
See where AI speeds up delivery and where it adds risk.
CodeDD tracks AI use and code review in every portco. Company C writes 44% of its code with coding agents and ships over half of it unreviewed. Its 27% change fail rate is the likely result.
- AI-written code counts only commits that name a coding agent, so each share is a floor.
- Company D shows n/a because its Git host does not expose review data. Missing data is never counted as a shortfall.
Portfolio AI in development
Last 90 days · five portfolio companies| Metric | Company A | Company B | Company C | Company D | Company E |
|---|---|---|---|---|---|
| Adoption | |||||
| AI-written codeshare of lines | 38% | 26% | 44% | 3% | 17% |
| Repositories with agent instructionsof repositories in scope | 9 of 12 | 5 of 10 | 2 of 14 | 0 of 6 | 3 of 8 |
| Review | |||||
| AI code merged unreviewedshare of AI-written lines | 4% | 6% | 58% | n/a | 11% |
| Open AI pull requestsunreviewed / total | 2 / 14 | 1 / 9 | 23 / 31 | 0 / 0 | 4 / 12 |
The audit rhythm
Annual baseline audits, regular monitoring in between.
Each portfolio company gets a full audit once a year. Lighter quarterly and monthly checks track movement against that baseline until the next one.
Annual baseline
One full audit per portfolio company, covering 100% of the codebase. It sets the reference point for the year.
Annual full audit
Quarterly monitoring
An analysis of the 100 most active files in each portfolio company. It tracks movement against the baseline and feeds the quarterly board pack until the next full audit.
Quarterly monitoring
Monthly pulses
Lightweight monthly data on development activity, delivery metrics and team signals.
Monthly pulses
Connect your Git host
GitHub
GitLab
Azure DevOps
Bitbucket
FAQ
Questions operating partners ask us.
Which measures does the portfolio view include?
Code quality across seven dimensions, delivery through the five DORA metrics, AI in development, and key-person risk. Each uses the same definitions as the individual product views and is applied the same way in every company.
How do portfolio companies connect?
Each company grants read-only access to its Git host: GitHub, GitLab, Azure DevOps or Bitbucket. There is no agent to install and no survey to fill in.
How current is the data?
Delivery data syncs from Git every day. The view shows when each company last synced and flags anything older than 48 hours.
Can companies with different release models be compared?
Yes, with context. A company whose customers install the software may release quarterly and rate Low on deployment frequency. That can suit the business, so read each company's metrics against how it delivers to customers.
Do you rank individual developers?
No. The view reports on repositories and companies. It does not score or rank individual engineers. Contributor data can also be fully anonymised to meet local data protection policies.
What data do you store?
Structured results such as deploy events, review linkage, AI-authored line counts and ownership shares. Not source code.
See your portfolio on one set of measures.
Speak to our team to see how CodeDD can automate and support your technology value creation plan.