[ Agentforce & AI ]
Agentforce, built to ship — not to demo.
We design service and sales agents that resolve real cases end to end: grounded in your data, scoped to safe actions, and measured on deflection and CSAT from day one.
[ the problem ]
Why most Agentforce pilots stall
An agent demos beautifully on three clean records, then meets production and either refuses to act or confidently invents a policy that does not exist. The gap is never the model — it is the data it can retrieve, the actions it is allowed to take, and whether anyone is measuring the outcome.
[ how we solve it ]
What you get from MindBlaze.
Grounded in Data Cloud
We connect the agent to your real records, knowledge, and policies through Data Cloud so every answer is retrievable and citable — not a generic chatbot bolted onto your org.
Scoped topics & governed actions
Tightly defined topics map to deterministic Flow and Apex actions with explicit guardrails and escalation. The agent decides whether; your platform decides how, the same way every time.
Measured on outcomes
Deflection, resolution time, escalation quality, and CSAT are instrumented before go-live, so the launch is the start of a tuning loop — not the finish line.
[ representative results ]
Illustrative outcomes · client references available under NDA
[ what's included ]
Deliverables
- A production Agentforce agent (Service or Sales)
- Data Cloud grounding & retrieval setup
- Topic, action, and guardrail configuration
- Outcome dashboards and a tuning playbook
[ how it runs ]
Process
- 01
Map
We map the highest-volume use case, the data behind it, and what “resolved” means.
- 02
Build
We wire grounding, topics, and actions in a sandbox and adversarially test it.
- 03
Tune
We launch to a slice, watch transcripts, and tune topics and grounding to target.
[ questions ]
Agentforce & AI — answered.
How is this different from a Salesforce chatbot?
A chatbot answers from a script. An Agentforce agent retrieves from your Data Cloud and takes governed actions — issuing a refund, updating a record, booking a slot — then escalates with full context when it should not act.
Do we need Data Cloud first?
Not always, but grounding quality is the single biggest predictor of a useful agent. If your data is thin, we get the model and grounding right before scaling topics.
How do you prevent hallucinations?
Narrow topics, retrieval-grounded answers, explicit “I do not know — let me get a human” paths, and adversarial testing before launch.
How long to a first agent?
A focused first agent typically goes to a sandbox in weeks, not months — then tunes in production against real transcripts.
[ let's talk ]
Ready to scope your agentforce & ai project?
Tell us what you are trying to do. You will talk to the delivery team — not a sales script — usually within one business day. No slide deck, just a working session.