A practical guide to the Salesforce AI API (and a simpler alternative)

If your business runs on Salesforce, you’ve probably seen the buzz around Einstein and the Salesforce AI API. The pitch is compelling: automate tasks, write content, and find hidden gems in your data, all without leaving your CRM. But let’s be honest, going from a slick demo to a working tool can be a bit of a journey. Tapping into Salesforce AI often means wrangling complex setups, looping in developers, and getting way more familiar with APIs than you might have planned.

This guide is here to give you a straight-talking, practical look at the Salesforce AI API. We’ll cover what it is, what it does, and what you really need to consider before diving in. We’ll also be upfront about its limitations and show you a much simpler way to get powerful AI automation up and running, without the technical headaches.

What is the Salesforce AI API?

First off, the Salesforce AI API isn’t one single thing you just switch on. Think of it more like a developer’s toolkit that lets you plug Salesforce’s AI brain, Einstein, into your own apps and workflows. It’s built to give you access to powerful Large Language Models (LLMs) to do all sorts of smart tasks.

For anyone with a technical background, the main way in is through the Models API. You can talk to it using either REST (a common web standard) or Apex (Salesforce’s own coding language). This API acts as a gateway to different LLMs, including some from partners like OpenAI. Everything passes through a security checkpoint called the Einstein Trust Layer, which is a nice touch. It’s designed to do things like mask sensitive customer data before it ever gets sent to an AI model.

The API gives you a few key abilities:

• Generate Text: Great for one-off tasks like summarizing a case file or whipping up a first draft of a sales email based on a prompt.

• Generate Chat: This is what you’d use to build a back-and-forth chatbot experience, since it can remember the conversation history.

• Generate Embeddings: This one’s a bit more technical. It’s used for "semantic search," which is a fancy way of saying it turns text into numbers to find things that are conceptually similar, not just matching keywords.

So, at its heart, the Salesforce AI API is a set of building blocks for developers who want to weave generative AI directly into the fabric of their Salesforce setup.

Core Salesforce AI API capabilities and common use cases

Okay, so what can you actually build with this thing? The main idea is to help your team get more done by automating the tedious bits of sales, service, and marketing. Since the AI can pull from your CRM data, the results it gives back can be incredibly relevant.

Here are a few of the most popular ways people are using it:

• Automated case summarization: This is a big one. Instead of having agents read through endless email chains and notes, the AI can create a quick, clean summary of a customer support case. It’s a huge time-saver that gets agents up to speed in seconds.

• Drafting sales and service replies: The API can write personalized email replies for your sales team’s outreach or your support team’s responses. It uses the customer’s history in the CRM to make the message feel tailored and relevant.

• Predictive analytics: While Salesforce packages some of this in its Einstein products, you can use the API to build custom tools that spot patterns in your data. Think predicting which customers might be about to leave or which leads are most likely to convert.

• Content generation for marketing: Your marketing team can use the API to get a head start on writing ad copy, product descriptions, or social media updates, all using the information you already have stored in Salesforce.

These are all powerful applications, but it’s important to remember that building them isn’t as simple as just writing a prompt. It involves creating a whole process that pulls the right data, sends it to the API in the right format, interprets the AI’s response, and then displays it in a useful way to your team.

The fine print: Setup, pricing, and key considerations for the Salesforce AI API

This is where the rubber meets the road. Using the Salesforce AI API isn’t a simple flip of a switch; it requires a real technical setup and a good grasp of how you’ll be charged.

The Salesforce AI API setup process

Unless you’re a developer or a highly technical Salesforce admin, you’re going to need help. You can’t just turn it on in the settings. You have to carefully configure how your app will securely talk to Salesforce.

The process looks something like this:

1. Create a Connected App: This is like registering your application with Salesforce so it knows to trust it.

2. Configure OAuth 2.0: You have to set up the authentication rules and tell Salesforce exactly what your app is allowed to do (these are called "scopes").

3. Generate a JWT: Your application will need to create a special security token to prove its identity with every single request it makes. This means managing secret keys securely.

4. Write the code: Someone has to write the actual code that calls the API, processes the answers, and handles any errors that pop up along the way.

Salesforce AI API pricing

Salesforce’s pricing for AI can be a bit of a maze. It’s often bundled into different product tiers or sold as add-ons. The model is typically based on usage, which revolves around "Einstein Requests" or credits.

• Einstein 1 Platform: Access to these AI tools is often part of the higher-tier Einstein 1 Platform edition or an add-on you have to buy. For instance, the Einstein Generative AI Add-On for Sales or Service Cloud gives you a starter pack of credits.

• Usage-Based Credits: Many features eat up credits every time you use them. An action from the Einstein Copilot might cost a certain number of credits, for example. This makes budgeting a real challenge because your costs will go up and down with user activity.

• MuleSoft: Need to pull in data from outside Salesforce to give your AI more context? You might need a MuleSoft subscription, which can be another hefty expense.

This model can be unpredictable. If your support team has a really busy month, you could be looking at a surprisingly high bill. That’s a big deal for any business trying to keep costs in check.

Limitations and challenges of the Salesforce AI API

While the Salesforce AI API promises deep integration, it comes with some serious drawbacks that can make it a slow, expensive, and frustrating path to AI automation.

1. It’s a full-time job for your developers

From the initial setup to building out a single new feature, the whole process leans heavily on developers. This creates a bottleneck for your other teams, slows down any new ideas, and racks up costs for both the initial build and ongoing maintenance. If you want to tweak a prompt or adjust a workflow, you’ll probably have to get in line and file a ticket with the engineering team.

2. It’s limited to your Salesforce data silo

Salesforce AI is at its best when it’s using data that’s already in Salesforce. But where does most of your company’s real knowledge live? For most of us, it’s scattered across places like Confluence, Google Docs, Notion, or Slack. Trying to connect these outside sources with the native API is a huge project on its own. It usually means buying and implementing another complicated tool like MuleSoft, which just adds more cost and complexity. Your AI’s answers are only as good as the information it can access, and keeping it stuck in Salesforce is a major handicap.

An infographic showing how eesel AI connects to multiple knowledge sources like Salesforce, Confluence, and Google Docs to provide comprehensive AI answers, overcoming the limitations of the Salesforce AI API.

3. There’s no easy way to test and simulate

How do you know if your new AI-powered workflow is actually going to help? With the native API, there’s no "simulation mode" to test it on your past support tickets. You just have to build it, launch it, and hope for the best. This makes rolling out new automation pretty risky, since you can’t predict how well it will perform or how it will impact your customer satisfaction before it’s live.

A screenshot of the eesel AI simulation mode, which allows users to test their AI agent against past tickets to forecast performance, a key advantage over the Salesforce AI API.

4. Rigid workflows and limited control

Want to build smart, flexible workflows? Get ready for some serious custom coding. For example, say you only want an AI agent to handle simple "where is my order?" tickets but pass anything about billing to a human. Creating those kinds of specific rules in Apex or Salesforce Flow is complicated. You often end up with a rigid, all-or-nothing automation that just doesn’t fit the way your business actually works.

A screenshot of eesel AI's no-code workflow builder, demonstrating how easy it is to set up custom rules and guardrails compared to the complex coding required by the Salesforce AI API.

A simpler, more powerful alternative: eesel AI

If all those challenges sound like a project you don’t have the time or budget for, you’re not wrong. But there’s a better way. Instead of pouring months and a small fortune into a custom-coded solution, you can get all the benefits of AI automation in a fraction of the time with eesel AI.

eesel AI was built to solve the exact problems that native API integrations create. It’s a platform you can actually use yourself, putting the power of AI directly into the hands of your support and IT teams, with no developers needed.

Here’s what makes eesel AI different:

• Go live in minutes, not months: You can forget the endless sales calls and complicated setups. Just connect your helpdesk (like Zendesk, Freshdesk, or Salesforce Service Cloud) and other knowledge sources with a single click and build your first AI agent on your own.

• Connect all your knowledge instantly: eesel AI plugs right into Salesforce and all your other sources of truth, Confluence, Google Docs, past tickets, Slack, right out of the box. Your AI gets the full story, which means it gives much more accurate and helpful answers.

• Test with confidence: Our powerful simulation mode lets you run your AI against thousands of your past tickets before it ever talks to a real customer. You get clear forecasts on its performance and can tweak your setup with zero risk.

• You’re in complete control (with clear pricing): Our simple workflow builder lets you decide exactly which tickets your AI handles and what it’s allowed to do. And our pricing is straightforward and predictable. No confusing per-resolution fees, just simple monthly plans you can cancel anytime.

Feature	Salesforce AI API (Native Build)	eesel AI
Setup Time	Weeks to months	Minutes
Developer Required?	Yes, big time	No
Knowledge Sources	Mostly Salesforce data (others are hard)	Salesforce, Confluence, GDocs, Slack & more
Simulation Mode	No	Yes, on thousands of past tickets
Workflow Control	Heavy coding needed (Apex/Flows)	Simple, no-code workflow builder
Pricing Model	Unpredictable, credit-based fees	Transparent, flat-rate plans

Get started with smarter AI automation today

The Salesforce AI API is a capable tool if you’re deeply invested in the Salesforce ecosystem and have a dedicated team of developers ready to go. But for most teams who just want a fast, flexible, and affordable way to use AI, a native integration is full of hurdles.

By going with a solution like eesel AI, you can skip the complexity and get right to the good part. You get a smarter AI that learns from everything your company knows, the confidence to deploy it safely, and the control to automate things on your own terms.

Ready to see how easy AI can be? Start your free trial with eesel AI and you can build your first AI agent in less than five minutes.