What is Flow Engineering?
Flow Engineering is requirements management software for hardware teams, connecting requirements with systems engineering records. It describes a connected systems graph for requirements, interfaces, design artefacts and tests, with AI agents that help assess changes and prepare work for review. Its scope spans the records around a hardware programme rather than a standalone requirements document.
Arc publishes this source-based overview and has a commercial interest in teams choosing Arc. We reviewed Flow’s public product, pricing, integration and security material on 2 November 2026. This article identifies the software and routes you to practical evaluation resources. It contains no hands-on product test, independent rating or customer result.
How does the requirements model work?
Flow’s Requirements Management page describes requirements linked to the systems they govern, tests that verify them, interfaces they constrain and relevant standards. It supports decomposition from top-level intent into subsystem, component and interface requirements. Teams can configure entity types and typed fields rather than working only with a fixed document schema.
For an engineer, the useful question is what a relationship means. A parent-child link expresses decomposition. A link to an interface can express a constraint. A verification link should identify the activity intended to provide evidence. A collection of related records only supports a review when those meanings, revisions and owners are clear.
The documentation also describes source links when importing specifications, supplier documents and standards. In an evaluation, keep the original identifier and source revision alongside the new record. Check how a reviewer distinguishes the current engineering requirement from wording that appeared in an earlier source document.
Which teams is Flow aimed at?
Flow positions itself for hardware teams connecting CAD, simulation, code and test. That makes it relevant to multidisciplinary programmes in which electrical, mechanical, software, systems and verification contributors change related information. A space payload, autonomous vehicle or aviation subsystem can all create this kind of coordination need.
A small team buying its first dedicated tool needs a maintainable record model and a clear owner. A team replacing an installed system also needs accepted history, contractual outputs and integrations to survive the move. Those are different buying situations. The alternatives guide develops the shortlist and the reasons to retain an incumbent.
Industry positioning does not determine suitability for a particular programme. The customer’s review authority, configuration process, data restrictions and required deliverables set the conditions. A software review status cannot by itself establish flight readiness, safety acceptance or contractual compliance.
What can the systems graph tell a reviewer?
The homepage describes opening a node to see upstream dependencies and downstream impact. The Requirements Management page adds connected test and interface context. This can help a reviewer follow a changed requirement to the records already represented in the model.
Use two checks when evaluating that graph. First, can the reviewer recover the right record revision and explain the relationship? Second, what happens when an engineering dependency has never been recorded? A clean graph or coverage indicator cannot establish that every physical dependency has been captured.
The change-impact evaluation deliberately leaves one thermal relationship incomplete. Its fictional inputs let you inspect the difference between a known linked consequence and an unresolved dependency. The protocol supplies no executed outcome for either product.
Where do AI agents fit?
Flow documents agents that assess change impact, check test coverage, assist requirement authoring and compare records with programme standards. Its homepage also describes agents operating across connected engineering tools. The Branching page says that agents prepare work on branches and humans review before changes reach the baseline.
Evaluate an agent with a task whose answer can be checked. Ask it to identify the affected power analysis, explain its source context and retain an unresolved thermal question. Review the proposed fields and relationships before accepting them. A plausible explanation is insufficient evidence that the model or engineering assessment is complete.
For either vendor, agree enabled actions, the user or service identity, review authority and how agent actions are logged. Keep data processing and retention separate from permission to propose a change. Public AI claims provide the starting scope, while your selected environment determines what the team can use.
How are branches, reviews and baselines described?
Flow’s Branching page describes isolated workstreams, visible differences, required reviewers and merging reviewed changes into a baseline. It also documents timestamped immutable baselines, comparisons between baselines, branch permissions and product variants or configurations. These concepts are part of Flow’s documented scope.
A useful evaluation should show the accepted baseline beside the proposal, a rejected or returned change, the resulting reviewer record and any open action. Inspect who may propose, review, merge or administer the work. Check exception paths in the selected configuration rather than assuming that a product-level statement describes every permission route.
Flow also documents branch-scoped PDF, DOCX and CSV exports. Confirm which records, revisions, relationships and review context appear in the package you need. A named file format does not establish preservation of all history or a complete machine-readable round trip.
Which integrations are documented?
| Connection | Scope described on 2 November 2026 | Evaluation question |
|---|---|---|
| Excel | Connect spreadsheets, retain versioning and check specific cell values against requirements. | Which workbook revision and cells are authoritative, and how is a failed check recorded? |
| Jira | Dynamically link tickets to requirements and show current status. | Which issue fields are read, and what does the status establish about engineering acceptance? |
| GitHub | Review pull requests with AI and enforce quality gates. | Which repository permissions and branch rules apply? |
| Onshape and Python | Retrieve model quantities and connect analysis results to requirements. | Can a reviewer recover the model or script revision and the conditions used? |
| Roadmap entries | Several integrations, including Ansys, Matlab and SolidWorks, are labelled Coming Soon. | Is the connection available in the proposed environment, with agreed scope and support? |
Inspect each connector’s permissions, triggers, direction and error handling. The wording “all integrations” in a plan table does not turn roadmap entries into delivered connections. Use the existing Excel guide and Jira guide for those boundaries.
What should be checked about plans and data?
Flow’s public pricing lists Basic at $150 USD per editor per month and Pro at $300, with Enterprise at custom pricing. Requirement, project and configuration limits differ. The dated plan table owns the detailed snapshot and commercial worksheet.
Flow’s Security page describes cloud, GovCloud and self-hosted deployment, private inference, no model training on customer prompts/documents/outputs and AI action logs. These are vendor statements. Confirm the actual deployment, processing locations, retention, access controls and supplied assurance evidence for your programme. This source review did not inspect certificates, contracts or an operating tenant.
Which evaluation resource should you use?
| Your decision | Use | What it produces |
|---|---|---|
| Does it support our next review? | Practical Flow review | A milestone checklist covering revision, configuration, provenance and accountable acceptance. |
| What will comparable scope cost? | Flow pricing | A dated plan snapshot and equivalent commercial scope worksheet. |
| What else belongs on our shortlist? | Flow alternatives | Six approaches, their constraints and incumbent retention conditions. |
| How does the documented workflow compare with Arc? | Flow vs Arc | The same requirements, change and evidence criteria applied to both products. |
| What could we ask a product to demonstrate? | Change-impact protocol | Fictional inputs, expected records and an explicit unresolved dependency. |
For Arc, the relevant mechanisms are the connected programme model, controlled changes and configuration-linked verification. Use the pairwise comparison to assess them beside Flow’s documented scope. Both products describe overlapping capabilities, so the decision should follow your required records and operating constraints.
Frequently asked questions
What is Flow Engineering?
Flow Engineering is requirements management and systems engineering software for hardware teams. Its public material describes a systems graph connecting requirements, systems, interfaces, design artefacts and tests, with AI agents and branches for proposing and reviewing changes.
Is Flow Engineering only for software requirements?
No. Flow positions its software around hardware programmes and connections across CAD, simulation, code and test. Software records can form part of that context, but the product is not described as a software-only issue tracker.
What does a systems graph add to a requirements list?
A systems graph stores relationships between a requirement and the records around it, such as its parent intent, allocated system, constrained interface and verification activity. Those links help reviewers inspect recorded context. Engineers still need to check relationship meaning, completeness and evidence applicability.
Does Flow Engineering use AI agents?
Yes. Flow documents agents for impact analysis, test coverage, authoring and checks against programme standards. Its Branching page describes agent work on branches with human review before baseline merge. That documentation does not establish agent accuracy, complete physical dependency discovery or approval for a particular programme.
Where should a team start its evaluation?
Define one review decision, the authoritative requirement set, required reviewer roles and the evidence configuration. Use the milestone checklist for fit, the dated pricing worksheet for commercial scope and the change-impact protocol for a fictional requirements-to-evidence exercise.