Agentic commerce vs.
the SaaS stack.

What the SaaS stack does well

The honest answer: a lot. Stripe is excellent. It handles payment processing, fraud detection, subscription management, and checkout with a reliability that would take years to replicate from scratch. Klaviyo handles email marketing for the median store better than most stores configure it to work. These tools exist because there is real value in standardized, maintained, continuously improved infrastructure.

The SaaS stack is the right answer for stores that are early-stage, growing quickly, do not have technical resources, or do not have a specific problem that requires non-standard behavior. If Klaviyo's default cart abandonment flow converts at 15% and that is acceptable, the SaaS tool is the right call.

What the SaaS stack does not do

It does not share context across tools. The cart abandonment email Klaviyo sends does not know what the Rebuy recommendation widget showed before the cart was abandoned. The post-purchase sequence in Aftersell does not know the customer's session history before the sale. Each tool operates in its own data silo. The actions are individually optimized but collectively uncoordinated.

It does not adapt to your specific store's behavior patterns. Klaviyo's abandonment flow is built for the average cart abandonment trigger. Your abandonment pattern may be driven by a specific shipping rate display, a specific product configuration page, or a specific device/browser combination that your analytics have surfaced but that the tool cannot act on without significant custom configuration — if it can act on it at all.

It does not get cheaper as you scale. Klaviyo's pricing is contact-based. More customers means more cost. Rebuy's pricing is revenue-based. More sales means more fees. The SaaS stack is designed to capture value as the store grows — which is good for the vendors and less good for the owner of the store.

It does not produce owned infrastructure. After three years of paying for these tools, you have three years of access history and zero owned assets. The moment you stop paying, the capability disappears. This is the model the vendors prefer and the model you accept when you sign up.

What custom agents add to the SaaS layer

The interesting strategic question is not "SaaS vs. custom" as a binary — it is where custom agents add value on top of what SaaS does correctly.

Stripe stays. Payment processing is infrastructure. Rebuilding it is unnecessary risk. Stripe's fraud detection, regulatory compliance, and payment method coverage are genuinely valuable, and replicating them is not the right use of the build.

The behavioral layer gets replaced. The agents that use session data, purchase history, and catalog-specific logic to make per-customer decisions — these are the candidates for replacement with custom agents. Not because the SaaS tools are bad, but because custom agents can be trained on your specific behavior patterns, share context across the lifecycle, and run at fixed cost as volume scales.

The monitoring layer gets added. None of the SaaS tools provide a unified view of all agent activity across the commerce lifecycle. JARVIS is purpose-built for that — to show what every agent is doing, what signals they are acting on, and what the outcomes are. That visibility does not exist in the fragmented SaaS stack.

The honest comparison by use case

Cart recovery: Klaviyo's default abandonment flow vs. a purpose-built cart recovery agent. The SaaS tool sends a generic three-email sequence. The agent identifies the trigger (price friction, shipping cost, product confusion, interrupted session) and responds to that signal. For a store with a $300 average order value and 200 abandoned carts per month, improving recovery rate by 5 percentage points is $30,000 in annual revenue.

Product discovery: Rebuy or LimeSpot vs. a purpose-built discovery agent. The SaaS tools apply collaborative filtering (customers who bought X also bought Y). The agent applies catalog-specific logic combined with session context. For stores with complex catalogs or unusual purchase patterns, the SaaS approach produces mediocre recommendations; the agent produces relevant ones.

Post-purchase: Aftersell or a Klaviyo post-purchase flow vs. a purpose-built post-purchase agent. The SaaS tools run the same sequence for every customer. The agent runs different sequences based on what the customer bought, how they bought it, and what their session history suggests about their next need. For high-ticket products, that contextual difference is substantial.

SaaS tools build for the median customer at the median store. Your store is not the median. The gap between what a SaaS tool delivers and what a purpose-built agent delivers is exactly the size of the distance between your store and the median.

When the SaaS stack is still the right answer

Below $10,000/month in revenue, the SaaS stack is probably still the right answer. The data volume is too low to train contextually meaningful agents, the improvement delta is smaller, and the operational overhead of maintaining custom infrastructure is disproportionate.

For stores between $10,000 and $50,000/month, the Foundation build — one agent for one specific problem — is the right entry point. One well-built cart recovery agent or one product discovery agent can pay for the entire build within 90 days while keeping the rest of the SaaS stack in place.

For stores above $50,000/month with specific, known friction points across multiple stages of the commerce lifecycle, the Full Suite is the right evaluation. The SaaS costs at that revenue level are typically $2,000–$5,000/month, and the efficiency gains from contextually coordinated agents are larger.