9 Best CTO Dashboards for Development Teams in 2026

Most engineering leaders don't need another chart. They need to know where delivery is at risk, which projects are stalling, and whether the team is running hot before it shows up in a sprint retro. This list covers platforms built for CTOs and VPs of Engineering at startups who want that view without stitching together Linear exports, GitHub activity, and Slack check-ins by hand. Tools were selected and ordered based on how much genuine analysis they perform versus how much raw data they hand back, how broad their integrations are, and whether they account for human factors like morale and burnout alongside code metrics.

Quick Comparison

• Progress: best for CTOs who want interpreted risk and morale signals delivered to them; pricing is quote-based; the only tool here with an MCP server and Claude integration for natural-language queries.
• LinearB: best for teams wanting fast, automated DORA tracking tied to PR workflow; free tier available; unique for gitStream's codified PR automation rules.
• Swarmia: best for teams pairing metrics with self-directed process change; quote-based pricing; unique for team-authored working agreements on PR size and review SLAs.
• Jellyfish: best for CTOs justifying spend to finance and the board; quote-based pricing; unique for mapping engineering allocation directly to business initiatives.
• Faros AI: best for orgs with a platform team wanting custom metrics; quote-based pricing; unique for its open, extensible data model.
• Waydev: best for cost-justification and industry benchmarking; quote-based pricing; unique for benchmarking velocity and cost against industry data sets.
• Hatica: best for leaders prioritizing developer well-being; quote-based pricing; unique for flagging burnout from after-hours activity and meeting load.
• DX: best for organizations running formal DevEx research programs; quote-based pricing; unique for the published DX Core 4 framework.
• Axify: best for small to mid-size teams wanting fast setup; quote-based pricing; unique for prioritizing minimal configuration over depth.

1. Progress

Progress is an AI-native engineering intelligence platform built for CTOs and engineering managers who are tired of translating dashboards into decisions themselves. It pulls activity from tools teams already run, like Linear and GitHub, and continuously analyzes it to surface pre-computed signals: what's stalling, where deployment risk is building, and how the team is actually doing beneath the surface of ticket counts.

What sets it apart on this list is the depth of interpretation. Most engineering analytics tools stop at DORA metrics and cycle-time charts, leaving a CTO to figure out what the numbers mean. Progress does that analysis upfront, flagging stalled work and emerging risk before a status meeting forces the issue, and it lets you ask plain-language questions about engineering activity through an MCP server and Claude API integration rather than digging through filters.

• Flags stalled work and emerging risk automatically, so issues surface before they become sprint-ending surprises
• Scores deployment risk and change pressure from merge volume and code churn, giving early warning ahead of a rocky release
• Tracks team momentum, showing whether delivery is accelerating or slowing over time
• Reads morale and wellness signals, a layer most engineering tools ignore entirely
• Generates executive summaries on demand, useful for board updates or weekly leadership syncs
• Answers natural-language questions about engineering activity via MCP and Claude, instead of requiring you to build a query or a report

Setup involves connecting your GitHub and Linear (or similar) accounts; there's no need to run surveys or configure custom dashboards to get value on day one. It's designed for a CTO or eng lead to run directly, without needing a dedicated ops analyst. The tradeoff is that it's most valuable to teams already standardized on GitHub and Linear-style workflows; organizations on very different or highly fragmented toolchains will get less out of it until their setup aligns better. Pricing is quote-based as of 2026; check the website for current plans.

Best for: CTOs who want answers and risk flags delivered to them, not another dashboard to interpret.

2. LinearB

LinearB focuses on automating DORA metrics (deployment frequency, lead time, change failure rate, and time to restore) and surfacing PR bottlenecks before they slow a release. It's built for engineering managers who live inside pull request workflows and want automation baked into the process rather than a separate reporting layer.

Its standout feature is gitStream, which lets teams codify PR automation rules directly into their workflow, like auto-assigning reviewers based on risk or size, or gating merges that lack test coverage. That moves LinearB from passive reporting into active workflow enforcement, which few other tools on this list attempt.

• Automated DORA metrics dashboards that update without manual configuration
• WorkerB, a Slack bot that nudges reviewers on stalled PRs before they become bottlenecks
• gitStream rules that automate PR routing and gating based on your own criteria
• Investment profile tracking that breaks down where engineering time actually goes by project type

LinearB connects to GitHub, GitLab, Bitbucket, Jira, and Slack, and setup is relatively quick since most of the value comes from Git and PR data it can ingest immediately. It's typically run by engineering managers rather than a dedicated analyst. The limitation is that it leans heavily into Git and PR-level workflow metrics; it has little to say about qualitative team health, morale, or burnout, so a CTO wanting that human layer will need to pair it with something else. A free tier is available as of 2026, with paid plans quote-based.

Best for: Teams wanting fast, automated DORA metric tracking tied directly into PR workflow.

3. Swarmia

Swarmia combines Git and issue-tracker data with developer experience surveys, aimed at engineering leaders who want metrics paired with team-driven process improvement rather than top-down reporting alone.

The feature that separates it from the rest of this list is working agreements: teams set their own norms, like maximum PR size or review turnaround time, and Swarmia tracks adherence automatically. That reframes metrics as something the team owns and improves, not just something leadership monitors from above.

• DORA metrics and investment distribution dashboards for a standard delivery health view
• Developer experience surveys that capture qualitative signals numbers alone miss
• Working agreements that let teams codify and self-monitor their own PR and review norms
• Goal tracking tied to specific engineering initiatives, connecting metrics to what the team is actually trying to achieve

It integrates with GitHub, GitLab, Jira, Linear, and Slack, and setup is straightforward for the metrics side. The survey and working-agreement features, however, require ongoing team buy-in and cadence to stay useful; if the team ignores the surveys or stops enforcing the agreements, that half of the value disappears. It's usually run jointly by an engineering manager and the team itself rather than imposed solely from the top. Pricing is quote-based as of 2026.

Best for: Teams that want metrics paired with self-directed process improvement, not just leadership reporting.

4. Jellyfish

Jellyfish is built for CTOs who need to answer a very specific question from the board or finance: what is engineering spending its time and budget on, and how does that map to business priorities?

Where it fits

Jellyfish's core strength is tying engineering allocation and spend directly to business initiatives, producing reports non-engineering stakeholders can actually read. That's a different job than most tools on this list, which are built primarily for engineering managers rather than cross-functional reporting.

• Engineering allocation reporting that maps team time to specific business initiatives
• Headcount and budget planning tools for forecasting engineering costs
• DORA and delivery metrics dashboards covering standard engineering health indicators
• Roadmap and investment visibility built for non-engineering stakeholders to understand without translation

Setup and fit

Jellyfish integrates with GitHub, GitLab, Jira, Slack, and HR and finance systems, which reflects its cross-functional design. That breadth also means setup takes more effort than a lightweight Git-metrics tool, and it's usually configured with input from both engineering and finance or operations. It's built for larger, multi-team organizations; an early-stage startup with a single team will likely find it heavier than necessary. Pricing is quote-based as of 2026.

Best for: CTOs who need to justify engineering spend and headcount to finance and the board.

5. Faros AI

Its main limitation is upfront cost of effort: Faros AI is built on an open data model that supports ingesting from a wide range of engineering tools and building custom metrics beyond what ships out of the box, but realizing that flexibility takes real engineering investment.

That openness is also what distinguishes it here. Where most platforms on this list hand you a fixed set of dashboards, Faros AI is designed for teams that want to define their own metrics and pipelines, often because their existing toolchain or reporting needs don't fit a standard template.

• An open data model that ingests from a broad set of engineering and CI/CD tools
• Customizable DORA and SPACE-aligned dashboards built around your own definitions
• AI-assisted insights that surface delivery and quality trends across the ingested data
• Extensibility aimed at internal platform or data teams building their own reporting layer on top

Faros AI connects with GitHub, GitLab, Jira, PagerDuty, and CI/CD tools, and is typically run by a platform or data engineering function rather than a single engineering manager, since configuring the data model and custom dashboards is a real project, not a quick setup. That makes it a poor fit for a small startup team without spare engineering capacity to dedicate to the tool itself. Pricing is quote-based as of 2026.

Best for: Orgs with a platform or data team willing to invest in a highly customized metrics layer.

6. Waydev

Waydev ties Git activity to cost and benchmarks a team's velocity against industry data, aimed at CTOs who need to defend engineering spend and output in board-level terms rather than just report on sprint velocity internally.

The benchmarking angle is what sets it apart here. Rather than only showing a team's own trend lines, Waydev compares velocity and cost metrics against broader industry data sets, giving leaders an external reference point when a board member asks whether the team is performing well relative to peers.

• Engineering benchmarking that compares your team's velocity against industry data
• Cost-of-engineering reporting that connects Git activity to actual spend
• PR and commit-level analytics for a granular view of delivery activity
• Team and individual contribution reports for performance conversations

It integrates with GitHub, GitLab, Bitbucket, Azure DevOps, and Jira, and setup is centered on connecting Git data sources, which is generally quick. It's usually run by an engineering leader who needs the cost and benchmarking angle specifically. The tradeoff is coverage: Waydev has limited reach into qualitative team health or morale signals compared to survey-based tools like Swarmia or Hatica, and individual contribution reports can create friction if used for performance evaluation rather than team-level insight. Pricing is quote-based as of 2026.

Best for: CTOs who need cost-justification and industry benchmarking for board conversations.

7. Hatica

Hatica pairs standard delivery metrics with wellness and burnout signals pulled from calendar and Slack activity, aimed at engineering leaders who treat developer well-being as a leading indicator of delivery risk, not a separate HR concern.

Its differentiator is burnout detection: Hatica flags after-hours work patterns and meeting overload, catching a team running unsustainably before that shows up as turnover or a missed deadline. Few tools on this list treat calendar and communication data as a first-class signal alongside code metrics.

• Burnout and after-hours activity flags that surface unsustainable work patterns early
• Wellness pulse surveys that capture how the team is actually feeling, not just how fast it's shipping
• DORA and cycle-time dashboards covering the standard delivery health metrics
• Meeting load and calendar analysis that quantifies how much time is lost to meetings versus focused work

Hatica connects with GitHub, GitLab, Jira, Slack, and Google Calendar, and is generally run by an engineering manager or a CTO directly involved in day-to-day team health, rather than a data or finance function. Its main gap is business-level reporting: it doesn't map engineering work to initiatives or spend the way Jellyfish does, so a CTO needing that board-facing view will need a separate tool for it. Pricing is quote-based as of 2026.

Best for: Engineering leaders prioritizing developer well-being alongside delivery tracking.

8. DX

DX is built around the DX Core 4 framework, a published approach to measuring developer experience across four dimensions: speed, ease, quality, and impact. It's designed for organizations that want a research-grounded, recurring measurement practice rather than a one-off dashboard.

What makes it different

Unlike tools that build their own proprietary metrics, DX anchors its measurement in a framework designed for repeatable, organization-wide comparison over time, including benchmarking against other companies. That gives it credibility in conversations where leadership wants to know the methodology behind the numbers, not just the numbers themselves.

• The DX Core 4 framework, combining survey and system data across speed, ease, quality, and impact
• Structured developer experience surveys designed for recurring, longitudinal measurement
• Benchmarking against other organizations for external context
• Executive and team-level reporting views tailored to different audiences

DX integrates with GitHub, GitLab, Jira, and Slack, and is typically run by a dedicated DevEx or platform team, since getting value from the framework requires committing to a recurring survey and reporting cadence rather than a set-and-forget dashboard. That makes it a heavier lift than most startups need; it's built for larger organizations formalizing a DevEx research practice, not a five-person team wanting a quick pulse check. Pricing is quote-based as of 2026.

Best for: Organizations building a formal, recurring developer experience research practice.

9. Axify

Axify is a lightweight flow-metrics and DORA dashboard built for small to mid-size teams that want visibility fast, without a lengthy configuration process or a dedicated analyst to run it.

Its priority is speed of setup over depth of analysis. Where tools like Faros AI or Jellyfish ask for real implementation effort, Axify is built to get a team looking at cycle time and flow metrics within a short onboarding window, which matters for a startup that needs a dashboard now, not after a quarter of configuration.

• Quick-setup DORA and flow-metrics dashboards that work with minimal configuration
• Cycle time and bottleneck visualizations that highlight where work gets stuck
• Team-level delivery reports suited to a single team or a handful of teams
• Simple onboarding built for smaller teams without a dedicated ops function

It integrates with GitHub, GitLab, Jira, and Azure DevOps, and is designed to be run directly by an engineering manager without additional tooling expertise. The tradeoff for that simplicity is depth: Axify offers fewer AI-driven or qualitative insights than platforms like Progress, Swarmia, or Hatica, so teams that outgrow basic flow metrics or want morale and burnout signals will likely need to move to a more comprehensive tool later. Pricing is quote-based as of 2026.

Best for: Small to mid-size teams that want a simple, quick-to-deploy metrics dashboard.

Matching the Tool to Your Stage

If you want a single platform that interprets risk and morale for you instead of handing you charts to decode, Progress is the clearest fit, particularly if your team already runs on GitHub and Linear. If speed of setup matters more than depth right now, LinearB and Axify get a DORA dashboard in front of your team fastest. For larger organizations that need engineering spend tied to business initiatives or a highly customized metrics layer, Jellyfish and Faros AI are built for that scale and complexity. And if developer well-being and structured experience research are the priority, Hatica and DX both go deeper on the human side than a standard metrics dashboard does.

None of these tools are interchangeable once you look past the DORA metrics they all report. The real differences are in how much analysis they do for you, how much setup they demand, and whether they account for the people doing the work, not just the commits they produce. Learn more about our services to see how Progress applies that analysis to your own team's activity.