8 Best Engineering Team Capacity Planning Software Tools in 2026

Startup engineering leaders juggling sprint commitments, hiring plans, and burnout risk need a clear read on who has bandwidth and who's overloaded. Some tools answer that question by watching what actually happens in your codebase and ticket tracker; others ask you to manually assign people to projects and trust the math. Both approaches are legitimate, but they solve different problems: capacity planning is about matching available engineering time to committed work, while resource scheduling is about assigning specific people to specific projects. This list compares tools across both categories, weighing them on data source, forecasting depth, and fit for lean teams.

Quick comparison

• Progress: best for startup leaders who want capacity read from real GitHub and Linear activity plus morale signals; quote-based; the only tool here that pairs capacity inference with burnout early-warning signs.
• LinearB: best for Git-standardized teams; starting around $19/contributor/month; the only tool with a Slack bot that alerts on overload at the individual PR level.
• Swarmia: best for growing orgs formalizing workload norms; starting around $30/contributor/month; unique working agreements that make capacity limits enforceable, not just visible.
• Runn: best for multi-project teams needing classic visual scheduling; starting around $10/person/month; heatmap view of allocation across the whole team at a glance.
• Float: best for teams wanting fast, simple scheduling; starting around $6/person/month; drag-and-drop reassignment speed that's hard to match.
• Resource Guru: best for ops managers scheduling mixed technical and non-technical staff; starting around $5/person/month; automatic clash detection for double-booked people.
• Forecast: best for teams billing engineering time to budgets; quote-based; AI staffing suggestions grounded in historical throughput.
• Mosaic: best for teams layering forecasting on existing PM tools; starting around $9.99/user/month; scenario modeling for hires or canceled projects before they happen.

1. Progress

Progress is an AI-native engineering intelligence platform built for technical leaders who need to know where capacity is actually going, not where a spreadsheet says it should go. Instead of asking managers to log estimated hours or manually assign tickets, it ingests real activity from GitHub and Linear and continuously interprets it to surface who's stalled, who's overloaded, and where risk is building before it shows up in a missed sprint.

What sets Progress apart on this list is that its capacity signal is derived, not entered. Most resource planning tools are only as accurate as the assignments someone typed in last week. Progress instead looks at merge volume, code churn, ticket movement, and cycle patterns to infer workload pressure, then layers in a read on team morale and momentum that most engineering tools ignore entirely.

• Flags stalled work and emerging risk automatically, without anyone building a dashboard to spot it
• Scores deployment risk and change pressure using merge volume and code churn, so you see overload before it becomes a shipping problem
• Tracks team momentum to show whether delivery is accelerating or slowing, and surfaces morale signals alongside it
• Answers plain-language questions about engineering activity through an MCP server and Claude API integration
• Generates executive summaries on demand, useful for board updates or cross-functional check-ins

Setup is light for teams already on GitHub and Linear: connect the accounts and Progress starts analyzing existing history rather than requiring a new tracking habit. It's typically run by engineering managers or founders who need a fast read without babysitting a dashboard.

It's not built to be a drag-and-drop scheduler. If you need to visually reassign five engineers across three projects for next quarter, you'll want a scheduling tool alongside it. Pricing is quote-based as of 2026, so you'll need to contact sales for current plans.

Best for: Startup engineering leaders who want capacity read from real activity data plus early burnout warning signs.

2. LinearB

LinearB is an engineering metrics platform that grew out of DORA and cycle-time reporting and has since added workload alerting on top. It's aimed at engineering managers who already track delivery metrics and want capacity risk folded into the same view rather than managed in a separate tool.

Its distinguishing feature is WorkerB, a Slack bot that pings you when a specific pull request has stalled or when a contributor's workload pattern suggests overload. That immediacy is something none of the more scheduling-oriented tools on this list offer.

• Sends real-time Slack alerts tied to specific PRs so overload gets caught mid-sprint, not at retro
• Surfaces DORA metrics dashboards for deployment frequency, lead time, and failure rate
• Breaks down cycle time and code review patterns by engineer and by team
• Lets you build custom workflow automation gates that trigger on review or merge conditions

LinearB integrates with GitHub, GitLab, Jira, and Slack, and setup mainly involves connecting your Git provider and issue tracker; most teams are running with it inside a day. It's usually owned by an engineering manager or a platform team lead.

The tradeoff is scope: LinearB's capacity view is heavily Git-centric, so if a meaningful share of your work happens outside pull requests (design, infrastructure ops, customer support engineering), the capacity picture will be incomplete. Pricing starts free for small teams, with paid plans around $19 per contributor per month as of 2026; check the site for current tiers.

Best for: Git-standardized teams that want capacity alerts bundled with delivery metrics.

3. Swarmia

Swarmia targets engineering organizations that have outgrown ad hoc capacity conversations and want workload norms written down and tracked. It's less a dashboard tool and more a system for making capacity commitments explicit and measurable.

The feature that separates it from the rest of this list is working agreements: teams set explicit rules (max work in progress, review response time, meeting-free blocks) and Swarmia tracks adherence automatically, turning capacity norms into something the team actually holds itself to.

• Enforces working agreements around WIP limits and review SLAs so capacity norms don't quietly erode
• Reports effort allocation at the initiative level, showing what percentage of team capacity is going to which strategic bet
• Runs developer experience surveys to catch qualitative strain that ticket data misses
• Shows cost-of-delay and investment balance views for weighing tradeoffs across competing priorities

Swarmia connects to GitHub, GitLab, Bitbucket, and Jira. Setup involves configuring the working agreements themselves, which takes more upfront thought than a plug-and-play dashboard; it's typically owned by an engineering director or VP of engineering rather than a single team lead.

That configuration overhead, combined with pricing around $30 per contributor per month as of 2026, makes Swarmia a heavier lift than a five-person startup usually needs. It's built for organizations with multiple teams and a real need to standardize practices across them.

Best for: Growing engineering orgs that want to formalize workload norms alongside investment tracking.

4. Runn

Unlike the activity-driven tools above, Runn is a resource and capacity planning tool built for teams that assign people to projects and need to see that allocation visually. It's aimed at project or delivery managers running several concurrent engagements at once.

• Renders visual capacity heatmaps by person and by week, so over- and under-allocation jump out immediately
• Supports scenario planning for hypothetical projects before they're greenlit
• Reconciles logged time against forecasted hours to show planning accuracy over time
• Provides a multi-project resource allocation view across the whole org

The heatmap is Runn's signature strength: rather than reading a table of assignments, you see color-coded blocks that make overload visually obvious across dozens of people and projects at once, something none of the pure engineering-metrics tools on this list attempt.

Runn integrates with Harvest, WorkflowMax, and CSV imports, and setup is mostly a matter of entering people, projects, and estimated hours. It's usually run by a project manager, resourcing lead, or delivery director, not the engineers themselves.

The catch is that Runn's picture of capacity is only as good as what gets typed into it. If assignments go stale or estimates don't reflect real effort, the heatmap will look clean while the team quietly drowns. Pricing is free for small teams, with paid plans starting around $10 per person per month as of 2026.

Best for: Teams juggling multiple concurrent projects who need classic visual resource scheduling.

5. Float

Float is resource scheduling software built for speed. It suits teams, engineering or otherwise, that need to reassign people quickly when priorities shift and don't want a heavyweight planning process getting in the way.

Its core strength is the drag-and-drop interface itself: moving a person from one project to another, splitting their week across two initiatives, or blocking out time off takes seconds, which matters when priorities change mid-sprint and the schedule needs to catch up immediately.

• Lets managers drag and drop assignments across people and weeks in real time
• Reconciles tracked time against the schedule to flag where plans and reality diverge
• Generates utilization reports by person and by team for retro conversations
• Tracks project budgets alongside the schedule so scope and staffing stay connected

Float integrates with Jira, Asana, Slack, and Google Calendar. It's lightweight enough that a single team lead or ops person can set it up in an afternoon and keep it current without dedicated admin time.

The limitation is that Float has no connection to actual code activity. It reflects what was planned, not what's really happening in the codebase, so a schedule can look balanced while an engineer is quietly buried in unplanned bug fixes. Pricing starts around $6 per person per month as of 2026.

Best for: Teams that want a simple, fast scheduling interface without deep engineering analytics.

6. Resource Guru

Resource Guru is scheduling software aimed at managers who oversee both technical and non-technical staff and need one clean grid for all of them, rather than an engineering-specific tool.

Its clash detection is the standout feature: it automatically flags when the same person has been booked on two things at once, a common failure mode when scheduling happens across multiple managers or tools without a single source of truth.

• Displays a color-coded scheduling grid that's easy to scan across teams and departments
• Manages leave and time off directly in the same view as project assignments
• Detects double-booked staff automatically and flags the conflict before it causes a problem
• Builds custom reports by project or by person for utilization reviews

It integrates with Google Calendar, Outlook, and Zapier, keeping setup simple: most teams are scheduling within it the same day they sign up. It's typically run by an operations manager or a team lead rather than requiring a dedicated resourcing role.

Resource Guru is intentionally lightweight, which means it offers little to no engineering-specific insight into code health, deployment risk, or delivery quality. It answers "who's booked on what," not "is the team actually healthy." Pricing starts around $5 per person per month as of 2026.

Best for: Ops-minded managers who need fast, simple scheduling across a mixed technical and non-technical team.

7. Forecast

Forecast combines project management, resource planning, and financial tracking, aimed at teams where engineering capacity decisions are also budget decisions, such as agencies or startups billing client work.

Where it differs

Forecast's AI staffing suggestions are grounded in historical throughput data rather than simple headcount arithmetic, so recommendations account for how a given type of work has actually gone in the past, not just how many hours are theoretically available.

• Suggests staffing based on historical throughput patterns rather than static hour totals
• Matches people to work based on tagged skills, not just availability
• Tracks budget and margin alongside every resource allocation
• Provides a portfolio-level capacity view across all active projects at once

Who runs it, and who it doesn't suit

Forecast connects to Jira, GitHub, Salesforce, and Slack, and is usually owned by a delivery or operations lead who also cares about margins, not just schedules. Setup takes longer than a pure scheduling tool because you're also configuring budgets and rate cards.

That breadth is a liability for teams whose only problem is capacity visibility. If you don't need margin tracking or client billing tied to staffing, Forecast will feel heavier than necessary. Pricing is quote-based as of 2026.

Best for: Teams billing engineering time to clients or cost centers who need capacity tied to budget.

8. Mosaic

Mosaic is a resource management platform built for teams that don't want to adopt a new tracker just to get capacity forecasting; instead it pulls utilization data from the PM tools already in use.

• Builds automatic utilization reports from data already sitting in Jira, Asana, and similar tools
• Models scenarios like a new hire, a departure, or a canceled project before it happens
• Tags people by skill and role to support better staffing decisions
• Compares forecasted utilization against actual utilization over time

Its scenario modeling is the differentiator: you can simulate the capacity impact of adding a hire or losing a project before committing to it, which turns capacity planning into a forward-looking exercise rather than a snapshot of the present.

Mosaic connects to Jira, Asana, monday.com, and QuickBooks, and is designed to sit on top of tools your team is already using, so setup is mostly connecting accounts rather than rebuilding workflows. It's usually run by a resourcing lead or operations manager.

The dependency on connected PM tools cuts both ways: if your Jira or Asana boards are poorly maintained, with stale tickets or missing estimates, Mosaic's forecasts inherit that noise. Pricing starts around $9.99 per user per month as of 2026.

Best for: Teams that want capacity forecasting layered on top of existing PM tools without adopting a new tracker.

Matching the tool to the problem you actually have

If the real question is whether your team's workload matches its actual output, not just whether a spreadsheet of assignments looks balanced, start with Progress. It reads capacity from real GitHub and Linear activity and pairs it with morale and momentum signals, so you catch overload before it shows up as attrition or a missed release.

If your problem is genuinely about assigning specific people to specific projects and seeing that allocation visually, Runn, Float, or Resource Guru will serve you better; they're built for scheduling, not for interpreting engineering signal. And if you want capacity folded into broader delivery or financial metrics you're already tracking, LinearB, Swarmia, Forecast, and Mosaic each bundle it with DORA metrics, working agreements, budgets, or existing PM data respectively.

Most startup teams eventually need both a read on real engineering activity and a way to schedule people against upcoming work. Start with whichever gap is causing the most pain right now, and don't mistake a clean-looking schedule for a healthy team. Learn more about our services.