Leah MessengerThe model is the same everywhere. Here are six things to ask AI agent platform vendors before you buy, plus a free RFP template to keep score.
Every AI agent platform looks good in a demo. It’s AI; it does something new every day, it’s impressive. However, the differences show up later when you start asking about the unglamorous stuff: how it learns your brand, who approves its work, and what the bill looks like once your whole team is using it.
They all have access to the same frontier models, so what exactly sets one platform apart? Quick answer: it’s everything built around the model. Longer answer: this blog.
An AI agent platform is software for building, running, and governing AI agents, meaning AI that can take a goal, plan the steps, use tools and data to carry them out, and check the result before handing it back.
The model at the center is only part of it. What the platform adds is the AI harness: the context, tools, checks, and human oversight wrapped around the model. A direct LLM is a very clever intern with no access to anything, while an agent platform gives that intern your instructions, your systems, a manager, and an audit trail. That sounds better, doesn’t it?
Most agent platforms bring together the same core pieces:
Context: the knowledge, rules, and examples agents draw on in every run
Tools and integrations: connections that let agents read from and act in other systems
Orchestration: multi-step workflows that run on demand, on a schedule, or when something changes
Governance: evaluations, approval steps, guardrails, and a record of everything each agent did
Usage and cost controls: visibility into what each agent, team, and workflow consumes
An AI agent platform for marketing puts that same foundation to work on marketing-specific jobs: researching, drafting, auditing pages, personalizing content, and reporting on what performed.
What changes is what fills the harness. The context is your brand (things like your style guide, tone of voice, audience, and the legal stuff). The tools are the systems your team already runs on, such as your CMS, CRM, DAM, and analytics. The checks are the ones marketing work needs, like brand, legal, and accessibility reviews, plus an approval step before anything is published or sent.
For example, Mark (Optimizely’s AI) comes complete with out-of-the-box agents and skills that are ready to go and pre-built for marketing work. Marketers can even build and manage their own agents and agentic workflows, without waiting on a developer (or adding to your developers’ almighty to-do list).
No surprises here, but marketing and digital teams are being asked to do more, at scale, with no additional headcount. Make it make sense, right?
Point solutions and chat windows help individuals, but they tend to break when the same task has to work across a whole team, brand, or region.
An agent platform purpose-built for marketing helps you:
Clear content bottlenecks: Agents take on research, drafting, search optimizations, and routing so work moves from brief to publish faster
Save time and agency fees: Recurring tasks like weekly reports and page audits stop depending on one person remembering to do them
Stay on brand and on policy: Brand, legal, and accessibility checks run on every asset before it goes live, not after a customer spots a problem
Personalize without the manual grind: Create and maintain variants for every audience, with the same governance on the thousandth version as the first
Get answers faster: Ask questions of your performance data in plain language instead of waiting on an analyst
Keep AI spend predictable: See what every agent, team, and workflow costs, and stop paying premium rates for simple jobs
An AI agent platform RFP (request for proposal) is a structured set of questions you send to shortlisted vendors so they all answer the same things, in the same format, with evidence. It turns “that demo looked impressive” into answers you can score side by side and then check in a trial.
Our free template does the heavy lifting. It includes nearly 300 vendor questions, a requirements workbook for your own team, shared capability definitions, and a weighted scorecard that compares vendors for you.
Plenty of products are a thin layer over someone else’s model. Find out what the vendor actually built, how it chooses and updates models, and how your brand knowledge gets into every run so nobody is pasting the style guide into prompts every. single. time.
Ask vendors:
Go under the hood of Optimizely’s AI, Mark, and see what privacy, governance, and guardrails look like.
An agent that can only answer questions you ask is, essentially, just a chatbot. Look for agents that read from and write to other systems in your tech stack (e.g., your CMS and analytics), run multi-step work on schedules or triggers, and can be built by marketers (no code or developer required).
Ask vendors:
Autonomy is great until something goes live that shouldn’t have. Otherwise known as a marketer’s nightmare. You want every run scored against criteria you set, approval gates before anything is published or sent, guardrails against prompt injection, and a full trace of what each agent did.
Ask vendors:
AI for everyone is actually AI for no one. Not full departments anyway, and certainly not vast enterprise-level marketing teams. Check for marketing-specific capabilities: compliance audits on drafts and live pages, personalization that publishes variants (not just drafts copy), SEO and AI search visibility, and Virtual Teammates that own recurring jobs.
Ask vendors:
Your finance team’s number one question will (and always will be) “What’s the expected ROI of this investment?” It’s a tale as old as time, so ask how usage is metered, whether failed runs are billed, and how the platform connects content to the traffic and revenue it drove.
Ask vendors:
Here’s how we built a prompt router that knows when to think less (because not every question deserves a PhD-level, expensive answer).
The best platform still needs people to get you live and a company that will still be innovating in three years. This is where implementation support, references, data terms, and security certifications come in.
Ask vendors:
These six areas give you the shape of a strong evaluation, and the full template gives you everything you need to run one: nearly 300 vendor questions, a requirements workbook for your team, and a scorecard that weights every answer by what matters most to you.