Agentforce
Pilot

An Agentforce pilot puts one agent into production for one use case on one channel, with a baseline measured before launch and exit criteria agreed in advance. It is a real agent handling real requests, not a demo, and it ends with evidence to decide whether to expand, adjust or stop.

Keeping it narrow matters. Each extra channel, action or data source adds design and testing, and Salesforce notes that AI features and agent testing can lengthen an implementation. A single, well-measured use case gives a clear answer sooner.

A good pilot use case is frequent, has a measure you already track, depends on data and knowledge that are in good shape, and has a safe fallback to a person. Answering common service questions from knowledge articles and following up inbound leads are typical examples Salesforce describes for service and sales agents.

Confirm the use case and record the baseline, prepare the data, knowledge and agent user, design the agent's instructions and guardrails, build its actions, test it in a sandbox with Testing Center, deploy it to production on one channel, then run and measure it against the baseline before the expansion decision.

In a sandbox, with Salesforce's Testing Center running batch tests that pair example requests with expected responses and show which subagents and actions the agent picks, plus manual checks in Conversation Preview. We test core requests, edge cases, hand-offs to people and requests for data the agent must not reach.

Trailhead advises running tests only in a sandbox because testing can change CRM records, and notes that testing consumes credits as customer use does, so the test set is sized to the use case. Before launch, Salesforce's deployment steps include creating the agent user in production, assigning its permission sets, confirming Einstein, Agentforce and Data 360 are enabled, checking flow versions and confirming the agent is active.

In scope: one agent, one use case, one channel, the actions and grounding that use case needs, the agent user and permissions, testing, deployment, measurement and a readout. Out of scope: further use cases or channels, new integrations beyond the use case, large data migrations and organization-wide change programs.

If grounding needs several sources or real-time data, the advanced Data 360 setup is scoped separately with Techila's Data 360 practice.

Against the baseline recorded before launch, using the same measure your team already reports, such as handle time, deflection or lead response time. Agentforce Observability adds session-level tracing, Agentforce Analytics, near real-time alerts and Quality Scores for relevance and helpfulness, which show why a result looks the way it does.

We review a sample of live conversations with the business owner during the pilot, fix instructions or actions where the agent misreads requests, and test each change in the sandbox before a new agent version is activated. Only one version of an agent can be active at a time, which keeps the comparison clean.

The agent should meet the target agreed against its baseline, hand off correctly when it should, stay inside its permissions, pass the agreed test set after every change, and have an owner on your side. If all are met, the next use case or channel is planned; if not, the readout says what to fix or whether to stop.

Scope, duration and price are set in a scoping call, because they depend on the use case, how ready the data is and how many actions the agent needs. Agentforce usage is billed by Salesforce separately; see the Agentforce pricing guide and the Agentforce cost calculator. To arrange the call, contact Techila.