Salesforce Agentforce

Most AI agents are demos that never reach a customer.

Agentforce makes it genuinely easy to build an AI agent on top of Salesforce. It does not make it easy to build one you would actually put in front of a customer or trust to update a record unsupervised. The distance between an impressive demo and a production agent is enormous, and it is almost entirely about grounding, tool use, evaluation, and governance, not about the prompt. That distance is exactly where our practice lives.

What we actually do

We design and ship production Agentforce agents on Sales Cloud, Service Cloud, Marketing Cloud, and custom apps. That means agent design and the tool use that lets an agent actually take action, evaluation so you know whether it is right before it goes live, human-in-the-loop workflows for the moments that need judgment, and governance so it stays inside the rules. The integration work with Data Cloud, MuleSoft, and external systems is what lets an agent move the work forward instead of just describing it.

Where Agentforce projects go wrong

The common failures: an agent grounded in messy data that answers confidently and wrongly, no evaluation so nobody can tell good output from bad, automation handed authority it should not have, and a pilot that demos beautifully and then quietly never ships because the production hardening was never scoped. We build the grounding, the guardrails, and the evaluation from the start, because those are the parts that decide whether an agent survives contact with real users.

Why Abstrakt Solutions

Our Agentforce work is grounded in real production deployments, not slide decks, and we are both a Salesforce Consulting Partner since 2017 and an Anthropic build partner. That combination matters: shipping an agent that works requires deep knowledge of the platform, the data underneath it, and the model on top. We build agents that do the work, with the controls that let you trust them to.