Elements.cloud vs Hubbl
Started in Org diagnostics. Two lines: Hubbl Org Intelligence for health, tech debt and security, and Hubbl Process Intelligence for process mining from record history. Raised a $6M Series A led by Salesforce Ventures in February 2026.
Choose Elements.cloud if you need to understand how your Org works today: what the configured processes are, how components connect, who has permission to access what, and what is and is not being used. Then act on it. Elements.cloud is strongest when discovery has to lead into structured design, dependency-aware change planning, documentation discipline and change governance. Choose Hubbl if your priority is technical-debt and Org-risk assessment: a fast, benchmarked, prioritised list of vulnerabilities, bad practices, documentation gaps and licence underutilisation. Hubbl is the fit if you do not need the same depth in process configuration, dependency-led impact analysis, or Agentforce design and governance. The key distinction, stated plainly: Hubbl helps teams find and rank Org issues. Elements.cloud helps teams understand the Org as a system and govern change across it. Plenty of customers run both. The last third of this article covers when that is sensible and when it is just two licences.
What Hubbl is built for
Hubbl assesses Org health, surfaces technical debt, and guides remediation. It focuses on three things: identifying complexity, risk and optimisation opportunities in the Org; prioritising remediation through issue and recommendation workflows; and cleaning up packages, code, connected apps, licences and permissions.
Hubbl Org Intelligence runs as an external scan with no managed package to install. That is a low-friction first read, and a real advantage over package-based tools. It produces a Hubbl Score and a Complexity Score across nine dashboards. The scoring method is published rather than hidden: high-severity issues get a logarithmic penalty, and the score is normalised against total metadata volume so Orgs of different sizes stay comparable. The structural point is not that Hubbl is shallow. It is that Hubbl's data model is an inventory of components and their attributes. That is exactly the right shape for scoring and ranking. It is the wrong shape for tracing consequences.
Configuration mining and process mining answer different questions
Both platforms help you understand how your Org really works. They disagree about what the source of truth is. Elements.cloud works from Salesforce configuration outward. Process Configuration Mining, surfaced in the product and the API as Org to Process, generates a lifecycle diagram for an object from its actual record types, lifecycle fields, automations, dependencies and permissions.
What we are built for
Elements parses the org into a resolved dependency, permission and change graph first, then reasons over it. Not "field A is used in flow B" but that flow B writes into field A, in an update-record element, on an after-save trigger, on a create operation. Traverses secondary, tertiary and further dependencies across more than a hundred Salesforce dependency types.
The proof point: The Dependency Explorer Grid separates a real consequence from a bare reference. A field can appear in 356 reports, but only two use it as a filter and have been run recently. That distinction is the whole job.
Choose Hubbl if
- Benchmarking. If you need to show leadership how your Org compares to the ecosystem, Hubbl’s scoring and benchmarking are purpose-built for that conversation and Elements is not
- Connected app and OAuth risk. Connected Apps Intelligence catalogues every connected app, tracks authorisation patterns and usage frequency, and flags risky permissions by name (ApiEnabled, AuthorApex, CanApproveUninstalledApps) with assignment data down to profile and permission set. That is specific, well-targeted security work
- Static code analysis. PMD for Apex and ESLint for LWC and Aura are proper engines, exposed through their API
- Process mining. If you already have field history tracking enabled on your key objects, Hubbl's variant analysis will show you where user activity diverges from the expected path and where time is being lost in a record's lifecycle. That is a strong input to deciding what to agentify. If your buying question is "how bad is it, and what should we fix first", Hubbl answers it faster than we do
Choose Elements.cloud if
- Elements.cloud is the better fit when your team needs more than isolated analytics or static documentation, when you need to understand change across process, metadata, governance and delivery risk in a joined-up way
- That includes teams that want dependency-aware impact analysis, automated and on-demand documentation, design-before-build, permissions assessment, and change governance that survives after the project ends
- It includes teams who need to answer "who has access to this field, and which combination of profile and permission sets grants it" as a routine question rather than an investigation
- It includes teams who need to know when that answer changes
- Access Change Monitoring polls the Setup Audit Trail every 5, 30 or 60 minutes and evaluates each change against your own policies
- Scoping is per policy, so a compliance lead watching admin-grade system permissions is not buried in field-level security noise on a sales object
- It is also the stronger fit if Agentforce design readiness matters
- Agent Finder classifies each activity in a process diagram as a conversational agent, an AI workflow, or deterministic automation
Questions to ask in your evaluation
- How well does the tool help me understand how my Org currently works end to end?
- Does it assess dependencies, or simply list components?
- Can architects, admins, BAs and product teams work in the same operating model, or is this primarily an assessment console?
- What happens to documentation after the initial project ends? Does it stay inside the change workflow?
- If I connect this to an AI agent, what can the agent actually ask? Get the tool list, not the demo
- What has to be true in my Org before this works: field history tracking, a specific permission, months of accumulated data?
Buying mistakes worth avoiding
- Treating a dependency list as impact analysis
- Knowing that a field appears in four places is inventory
- Knowing which of those four writes to it, in what order, and what fires afterwards is analysis
- Ask which one you are being shown
- Reading field population as field usage
- A 0% populated field can still be load-bearing across flows, layouts and reports
The honest verdict
Both products create real value, and they are optimised for different outcomes. Hubbl is the stronger fit when the priority is Org health assessment, technical-debt visibility, remediation prioritisation, connected-app governance, and getting to a defensible answer fast. It is Org-health-centric, it is well engineered, and for short- to medium-term clean-up and optimisation programmes it is hard to beat on time-to-value. Elements.cloud is the stronger fit when the priority is understanding and governing Salesforce change: process configuration discovery, metadata insight, dependency-aware impact analysis, documentation that stays current, and governance that holds across releases. It is built less as a one-time assessment and more as an operating model for running safer change across the business and technical layers. The decision is not which product has more dashboards, and it is no longer which one has an AI story, because both do. It is whether you need to find and rank your Org's issues, or whether you need a platform that can tell you what happens when you change one of them.
- AI explainers need the Org AI Analysis feature enabled on the space.
- Decision Engine is separately licensed.
- The MCP server is in closed beta.
- The AI-drafted backlog is draft only. It proposes stories, it does not write them into Elements.
- Shipped is not the same as switched on everywhere.
Comparison as of August 2026. Both products move quickly, so check the date before relying on any row.
Every comparison is an argument. A live Org is not.
See it run against real configuration and the question answers itself.