Propelo Alternatives After the Harness Acquisition

What changed when Harness acquired Propelo

Propelo was an independent engineering metrics platform that offered DORA dashboards, PR analytics, engineering health scores, and developer productivity reporting. It had a clear positioning in the mid-market: a purpose-built analytics tool that connected to GitHub, Jira, and a range of other engineering tools without requiring any other platform purchase.

Harness acquired Propelo in 2023 and rebranded the product as Harness SEI (Software Engineering Insights). The core features remained largely intact initially, but the acquisition created structural changes that matter to existing and prospective customers:

• Pricing now bundled with the Harness platform. Harness SEI is positioned as part of the Harness platform suite, which includes CI/CD, feature flags, chaos engineering, and cloud cost management. For teams that only want engineering metrics — and have no need for the rest of the Harness stack — the bundled pricing model creates unnecessary complexity and cost.
• Roadmap driven by enterprise platform priorities.Harness's target customer is large enterprises that want a unified DevOps platform. The roadmap for Harness SEI is now influenced by what enterprise Harness customers need, not what standalone engineering metrics customers need. Mid-market teams often find that the features most relevant to them move slower after acquisitions like this.
• Support tiers restructured. Propelo offered accessible support across its customer tiers. Post-acquisition, dedicated support and SLA guarantees have become more tightly coupled to enterprise contract levels, which smaller teams may not qualify for.
• Uncertainty about the standalone product path. When a standalone SaaS is acquired by a platform company, the acquired product either gets deeply integrated into the platform (losing its standalone appeal) or maintained as a secondary product with less investment. Either path creates uncertainty for customers who bought the original standalone value proposition.

Why Propelo users are evaluating alternatives

The teams most likely to explore alternatives fall into a few categories. Engineering teams at companies with 50 to 500 engineers who originally chose Propelo because they wanted engineering-specific analytics without committing to a large platform deal are now finding that the post-acquisition Harness SEI requires more organizational buy-in than they want to give.

There are also teams that evaluated Propelo but deferred the decision, and are now reconsidering in light of the acquisition. If you were going to buy Propelo as a standalone tool, the calculus is different when the product has been absorbed into a larger platform company.

Finally, teams that are Harness customers for CI/CD are evaluating whether Harness SEI is the right metrics layer or whether a purpose-built alternative provides better analytics depth for the same investment.

The best Propelo alternatives in 2026

1. Koalr — deployment risk prediction plus full engineering metrics

Koalr is a standalone engineering metrics platform built for mid-market engineering teams. It covers everything Propelo did — DORA dashboards, PR analytics, engineering health scores, custom metrics — and adds two capabilities that Propelo never had: deployment risk prediction and AI-powered analysis.

The deployment risk prediction is the differentiator that no other engineering metrics platform has matched. Koalr analyzes 32 signals across your PRs — change entropy, DDL migrations, test coverage delta, author file-expertise, SLO burn rate, and more — and produces a 0–100 risk score for every PR before it merges. That score posts as a GitHub Check, visible in your existing review workflow. Teams using it catch high-risk deploys before they become incidents.

Pricing is transparent and does not require an enterprise deal: free trial, then $39 per seat per month. There is no Koalr platform you have to buy the rest of. Koalr connects standalone to GitHub, Jira, Linear, Slack, PagerDuty, LaunchDarkly, and other tools your team already uses.

Best for: Engineering teams at 50–500-person companies that want purpose-built metrics, deployment risk prediction, and pricing that scales with their team.

2. LinearB — engineering metrics with workflow automation

LinearB is one of the more established engineering metrics platforms, with DORA metrics, PR cycle time analytics, and a workflow automation layer called WorkerB that can send Slack alerts for stalled PRs and suggest reviewers. It connects to GitHub, GitLab, Jira, and Linear.

LinearB's strength is its workflow automation — if you want your metrics platform to also trigger actions (alerts, routing, blockers), LinearB does that well. Its weakness relative to newer platforms is that it does not have deployment risk prediction or AI-powered analysis, so you get metrics but not forward-looking risk intelligence.

Best for: Teams that want workflow automation baked into their metrics platform and are willing to trade deployment risk prediction for PR routing features.

3. Swarmia — team health and developer experience

Swarmia positions itself around team health and developer experience rather than pure DORA metrics. It includes investment distribution reporting (how engineering time is split across features, bugs, and tech debt), developer surveys, and focus time analysis. DORA metrics are present but are not the primary organizing framework.

Swarmia is a good fit for engineering leaders whose primary concern is developer well-being and sustainable pace rather than delivery risk. It is less focused on deployment risk and change failure rate than Propelo was, so teams that specifically valued Propelo's DORA and delivery analytics may find Swarmia a partial fit.

Best for: Teams prioritizing developer experience and well-being metrics over delivery risk and DORA analytics.

4. Jellyfish — engineering-business alignment at scale

Jellyfish connects engineering data to business outcomes — what percentage of engineering capacity is going to which initiatives, how engineering investment maps to revenue impact, and executive-level delivery reporting. It is built for large engineering organizations where a VP of Engineering or CTO needs to present engineering ROI to a board.

Jellyfish has raised significant funding ($114.5M) and targets enterprise customers with 200+ engineers. For teams that chose Propelo for its mid-market accessibility, Jellyfish will feel over-engineered and over-priced. For teams at enterprise scale that need engineering-to-business ROI reporting, it is worth evaluating.

Best for: Large engineering organizations (200+ engineers) that need engineering ROI reporting for executive and board audiences.

5. Faros AI — data warehouse approach to engineering metrics

Faros AI takes a different architectural approach: it ingests your engineering data into a centralized data warehouse and lets you build custom dashboards, reports, and integrations on top of it. This gives you maximum flexibility if you have a data engineering team that can build and maintain the layer, but it requires more setup than a purpose-built SaaS tool.

Faros AI is best for organizations that have already built internal data infrastructure and want to add engineering metrics as one more data source, rather than teams that want a self-contained platform.

Best for: Data-platform-first organizations with engineering capacity to customize their metrics layer.

6. Cortex — internal developer portal with metrics

Cortex is primarily an internal developer portal — a service catalog, scorecard system, and self-service layer for platform engineering. It has engineering metrics features, but metrics are not the primary product. Teams that need a service catalog alongside their engineering metrics can evaluate Cortex, but teams that specifically need DORA analytics and delivery risk data will find Cortex a partial fit.

Best for: Platform engineering teams that need a service catalog and are willing to accept metrics as a secondary capability.

How to evaluate the alternatives

Before committing to any platform, verify these capabilities against your needs:

• Standalone pricing: Can you buy this tool without also purchasing a larger platform suite? Harness SEI is not the only tool that bundles pricing.
• DORA metric accuracy: Does deployment frequency come from actual deployment events or from merge events used as proxies? The distinction matters for accurate measurement.
• Historical backfill: Does the tool backfill 90+ days of history on first connection, or do you start from zero?
• Forward-looking risk: Does the platform give you any signal before a deployment fails, or only retroactive measurement after the fact?
• Integration breadth: Does it connect to your specific tool stack (Linear vs Jira, PagerDuty vs Opsgenie, LaunchDarkly vs Statsig)?

The bottom line

The Harness acquisition of Propelo was strategically logical for Harness but created uncertainty for mid-market Propelo customers. If you valued Propelo for its standalone positioning, purpose-built metrics focus, and accessible pricing, the post-acquisition Harness SEI is a materially different product.

The alternatives in the market have continued to evolve. Koalr in particular has added deployment risk prediction — a capability that Propelo never had — that makes the migration a genuine step up in analytics capability, not just a lateral move. If you're evaluating alternatives, that forward-looking risk intelligence is worth putting at the top of your requirements list.