Put your first AI agent to work on Salesforce in 6 weeks
We implement an Agentforce agent with focused use cases, clear guardrails and metrics from day one: it answers with your data, takes actions in the CRM and escalates to your team when needed.
A focused implementation, with clear guardrails and built to reach production.
Everyone talks about AI agents. Few have them running in production.
Between the hype, the demos and the pilots that never leave the sandbox, it's hard to know where to start. Without a focused use case, clear guardrails and metrics, AI projects drag on and never show value.
This QuickStart is designed to fix that: a real agent, in production, with a closed scope and price.
What this QuickStart enables
- Handle inquiries 24/7 with an agent that answers with your CRM data, not generic text
- Deflect repetitive inquiries and free up your team for complex work
- Take actions inside Salesforce: create cases, check statuses, book meetings
- Escalate the conversation to a person with full context when appropriate
- Define clear guardrails: what the agent can and cannot do
- Measure deflection, resolution and satisfaction with KPIs from day one
- Walk away with a foundation and a roadmap to scale to more agents and channels
Ideal for companies that need to
- Start with AI on their current Salesforce without a long project
- Relieve a support or sales team overloaded with repetitive inquiries
- Prove the value of Agentforce with a focused case before investing at scale
- Reach an MVP in production, not settle for another demo
- Stay in control: know what the agent does and when it escalates to a person
What's included
An initial scope designed to put an agent into production wisely.
- Discovery and design of 1 to 2 high-impact use cases
- Configuration of 1 agent in Agentforce (Agent Builder)
- Up to 10 topics with their instructions
- Up to 20 actions (Flows, prompt templates or existing Apex)
- Up to 5 Einstein prompt templates
- Knowledge base upload and connection for grounded answers
- 3 conversational flows mapped and implemented
- Human escalation criteria (guardrails)
- Deployment on 1 channel (web, Experience Cloud or internal)
- A testing round (UAT) and refinement with your team
- KPIs and a basic deflection and resolution dashboard
- 4 hours of remote training + documentation
- Assisted go-live and 30-day post-launch warranty
Estimated time
6 weeks
A QuickStart designed to go from hype to a real agent in production, with a defined scope and a focus on measurable results.
What makes this QuickStart different
An MVP in production, not a pilot
The goal is not a demo: it's an agent working with real users, with assisted go-live and a 30-day post-launch warranty.
Guardrails before promises
From the design stage we define what the agent can do, which data it answers with and when it escalates to a person. Friendly Technology applied to AI.
Metrics and a roadmap to scale
You finish with deflection and resolution KPIs, and a clear plan to add agents, channels and use cases without rebuilding what was delivered.
Worth keeping in mind
- Salesforce and Agentforce licenses are not included; AI conversation or credit consumption is contracted with Salesforce
- Requires an active Salesforce org (Service Cloud or Sales Cloud) and knowledge content provided by the client
- The QuickStart scope is focused and defined: additional agents, extra channels or complex integrations are quoted separately
- It does not replace a full implementation for highly complex or multi-agent scenarios
QuickStart investment
USD 5,500
Corresponds to the standard scope of the Agentforce QuickStart described on this page.
Payment terms
50% upfront to start the project and 50% upon completing the implementation.
Go from hype to a real AI agent, running on your data with clear guardrails.
- •Published prices are net amounts for AT Vault.
- •Taxes, withholdings and charges applicable in each country are not included.
- •Salesforce and Agentforce licenses, AI consumption, integrations not covered, custom development and scope extensions are quoted separately.