AI agents that close cases, not demos that impress in a boardroom.
What you get
- Agents grounded in live Salesforce records, not generic model output
- Explicit topics, instructions and guardrails with human-in-the-loop escalation
- Measurable case deflection and handle-time reduction from day one
- An AI governance model covering data access, PII, logging and review
What usually brings people to us
Pilots that never reach production
An agent that demos well on clean data and collapses on the messy reality of your service queue — because nobody defined what it is allowed to do.
Ungoverned AI access to customer data
Agents inheriting broad permissions, no audit trail and no policy on what leaves the org. That is a compliance incident waiting to happen.
No way to prove value
Without deflection metrics, response-time baselines and escalation tracking, AI spend is indistinguishable from a science project.
What we deliver
- 01
Use-case qualification
We score candidate use cases on data readiness, action complexity and measurable value, then build the one that pays for the programme.
- 02
Agent design & build
Topics, instructions, and actions built on Flow, Apex and Prompt Builder — with retrieval grounded in your objects, knowledge and external systems.
- 03
Data grounding
Knowledge article curation, Data Cloud or record-based retrieval, and the field-level access model that determines what the agent can see.
- 04
Guardrails & governance
Permission sets scoped to the agent user, escalation rules, response review workflows, logging, and an AI usage policy your compliance team can sign off.
- 05
Measurement
Baselines captured before launch, then dashboards tracking deflection rate, agent-assisted handle time, escalation reasons and answer quality.
Typical stack
- Agentforce
- Prompt Builder
- Einstein Trust Layer
- Data Cloud
- Apex invocable actions
- Flow
- Knowledge
- Einstein Bots
Agentforce & AI — common questions
No. Salesforce's Einstein Trust Layer applies zero-retention prompts and dynamic grounding, and we configure masking for sensitive fields. We document exactly what is sent, where it goes and what is logged.
Something high-volume, low-ambiguity and data-backed — order status, appointment changes, account lookups, or knowledge answers. An order-status workflow could retrieve live data and prepare a reply for an agent to review.
Not always. If the answers live in Salesforce records and Knowledge, standard grounding is enough. Data Cloud earns its cost when you need to unify data across systems.
Related services
Have a agentforce & ai problem worth solving?
Send us the specifics — current state, what has been tried, and what success looks like. You will get a considered technical response, not a brochure.
24/7 support — response within one business hour