Agentforce consulting for AI agents that do real work. With guardrails, a rollout plan and value you can measure.

Agentforce consulting is the work of planning, building and governing Salesforce AI agents so they do real work safely in production. In practice that means choosing the right first use case, getting the data and knowledge an agent will read into shape, designing topics, instructions, actions and guardrails, testing against real requests, rolling out in phases and measuring the result. SynconAI does that work as a certified Salesforce partner across the United States and Australia.

An Agentforce implementation covers readiness and use-case selection, data and knowledge preparation (with Data 360 where the agent needs unified customer context), a least-privilege running user, topics, instructions and actions in Agentforce Builder, the Flow, Apex and integration actions the agent calls, scored testing in Testing Center, a phased rollout with pilot exit criteria, and monitoring and tuning after go-live. SynconAI delivers each of those steps, and the step-by-step setup is set out in our Agentforce implementation guide.

Agentforce is Salesforce’s platform for building and running AI agents that use your CRM data, knowledge and governed actions to plan multi-step work, act and escalate to people with context. Salesforce now groups its AI portfolio under the Agentforce 360 name. What your org can turn on depends on product, edition, region and release, so we map Salesforce’s public roadmap to what you are licensed to run today.

It depends far more on your data and permissions than on the build. Configuring an agent is rarely the long phase; cleaning up the knowledge it will answer from and narrowing what its running user can see usually sets the real schedule. We start with a time-boxed proof of concept or pilot on one workflow, with exit criteria agreed up front, and give you a written, phased plan after discovery rather than a guess before it.

There are two separate costs. Salesforce sets the license and consumption price, and its models, including Flex Credits and per-conversation pricing, change by release, so confirm the current rate card with your account executive. Delivery is the second cost: SynconAI works through a one-time Technology Blueprint, monthly delivery plans or a fixed-scope Transformation program for significant AI implementations, all described on our pricing page. The cost most estimates miss is knowledge and data remediation.

Not for every use case. Data 360 is the current name for Data Cloud. An agent answering policy questions from Knowledge needs no data unification at all. An agent answering questions about one customer whose records live across several systems usually does, because the alternative is a live call into each system during the conversation. We decide per use case, and we deliver Data 360 programs when the agent needs that foundation.

Through configuration you can review, not through a prompt you hope holds. The agent runs as a user with least-privilege permissions, its topics and actions define what it may do, answers are grounded in approved sources, and refunds, deletions and other irreversible steps need a named human approval inside the action. Salesforce describes the Einstein Trust Layer as adding secure data retrieval, dynamic grounding, zero data retention, toxic language detection and an audit trail. We add change control, logging and a rollback plan your risk team can defend.

A traditional bot follows dialog paths someone designed in advance, so it handles the questions it was scripted for and little else. An Agentforce agent reasons over the request, picks the relevant topic, calls the actions it is permitted to use and escalates with context when the case is beyond its scope. Teams moving from bots usually keep the deterministic steps as Flows and let the agent decide when to call them.

No. Working rule-based automation should stay where it is. Flow is deterministic, testable and carries no per-run consumption cost, and replacing a working rule with a reasoning step makes it slower and less predictable. Agents earn their place where the input is unstructured language, where the paths cannot be listed in advance, or where an answer has to be assembled from several sources. The two work together: the agent decides, the Flow does.

AI automation in Salesforce combines an AI agent that understands an unstructured request with deterministic automation that carries out the steps. In practice an Agentforce agent reads the request, picks the topic and calls permitted actions, and those actions are usually Flows, Apex or API calls into other systems. SynconAI builds both sides, and keeps rule-based steps in Flow where they are cheaper and more predictable.

Common starting points are customer service on Service Cloud, sales on Sales Cloud, scheduling and technician support on Field Service, and internal agents for IT, HR and operations in Lightning, mobile and Slack. Marketing and commerce patterns are possible too. Exact attach points depend on your edition and product entitlements, which we check in discovery before anything is designed.

Ask how they test, not how they demo. A credible Agentforce partner will want to see your data and permissions before quoting, will agree pilot exit criteria up front, will build a scored test set before launch, and will name who owns the agent after go-live. Ask too whether they will tell you when Flow is the better answer. SynconAI is a Salesforce Select Partner, delivery is architect-led, and the team that builds version one stays on for the run state.

SynconAI is a Salesforce Select Partner and OpenAI Select Partner that designs, implements and runs Salesforce and Agentforce for clients in the United States and Australia. Its Agentforce consulting covers readiness, use-case selection, data and Data 360 grounding, agent design in Agentforce Builder, testing, phased rollout and managed support, delivered by certified architects who stay accountable after go-live.