Agents are only as good as the org they run on. Hubbl shows where your Salesforce org is ready for Agentforce and AI, where it isn't, and what to fix first. Then it gives every AI surface the same grounded context, so agents act on what your org actually is, not what it should be.
Duplicate fields, stale automation, undocumented metadata, and over-broad access barely slow a human down. An agent reads all of it literally. Put Agentforce on an org no one has cleaned up and you get wrong answers, risky actions, and a pilot that stalls before it ships.
One scan gives you a baseline on what decides whether agents succeed: least-privilege access, packages on current versions, fields in active use, and documented metadata. The Hubbl Score tracks it from there.
Findings are ranked by priority and effort, so the cleanup that matters most for AI goes first. Every fix comes ready to act on: a Jira ticket with the detail attached, or a prompt an agent runs in Salesforce.
Process Intelligence, part of Hubbl Enterprise, monitors your business processes on Salesforce and recommends which are a good fit for Agentforce, so your first agent starts where it can win, not where the request was loudest.
The Hubbl MCP serves current scan data to Claude, Slack, Agentforce Vibes, and your custom agents. Every surface asks and gets the same answer, grounded in what your org actually is. When it's time to act, Hubbl passes the fix to an agent or writes it up in Jira.
No matter the role or the goal, Hubbl follows one motion — turn the lights on, understand and act, then stay clean and get AI-ready.
A credential-free X-ray in about two minutes — inventory, security exposure, and process reality no admin could map by hand.
A ranked backlog with the fix attached to every item — ticket it, prompt it, or delegate it, and close tech debt at the speed of AI.
Continuous monitoring holds the line as the org evolves — and turns your ongoing work into a health score you can show.
The companies getting value from agents did the unglamorous work first: clean access, current packages, documented metadata. Hubbl makes that work measurable, ranks it, and hands your agents the context to do theirs.
"The board wants an AI plan, and I'm not sure the org can support one."
A readiness baseline and a ranked plan to close the gap.
"Our Agentforce pilot keeps getting it wrong."
Find the metadata and access problems behind the wrong answers.
"I need to pick a first use case that will work."
Process recommendations that point to where agents can win.
Same platform, pointed at your job. Here's where to go deeper.
Placeholder metrics — swap for real Hubbl data.
Get a readiness baseline, a ranked plan, and grounded context for every agent you build next.