getachilles.ai
success
Claude Code
intent
What does getachilles.ai do and who is it for? Explain it back to me.
7steps
41.0sduration
$0.3700cost
24,608tokens
8 steps1 reasoning step2 searches
home
docs
docs
/contact
search
search
home
80%
answer from your site
60%
answer efficiency
100%
followed site links
answer sources
- from this site80%
- from agent knowledge20%
url discovery
- given in the task20%
- followed a link80%
insight
Agent successfully gathered a coherent explanation of Achilles' positioning, target market, and differentiation, but pricing information remains opaque by design—the site does not publish pricing publicly and requires sales contact. The agent filled gaps in task comprehension (what 'different from alternatives' means) partly through model inference rather than site-provided competitive comparisons.
- ›Site content (steps [0], [2], [6]) clearly articulated what Achilles does, who it targets, and how it differs (speed, flexibility, dual AI+engineering model, governance), but deliberately obscured pricing behind a contact/request-access wall—step [6] confirmed no public pricing tiers exist.
- ›Step [1] (/pricing) and [3] (/contact) both returned 404s, indicating the site does not surface pricing or contact routes via standard URLs; the homepage had to be re-fetched to locate request-access and demo links.
- ›Agent's "How It's Different" section is grounded in site content (steps [0], [2]), but the "Confusing or Missing" section about lack of direct competitor naming relies on model inference that competitors (SAP Ariba, Coupa, EcoVadis) were mentioned in web search results [5] but NOT on the Achilles site itself—the agent correctly identified this as a site gap rather than claiming the site covered competitors.
- ›Web search [4] for pricing returned only a generic homepage snippet and links to unrelated AI pricing pages, confirming pricing is not indexed or surfaced externally; search [5] returned competitors for a different Achilles product (supply chain compliance platform by Achilles UK Ltd., founded 1990), not NOEIN Labs' manufacturing procurement tool—site discovery friction is high.
- ›Agent successfully distinguished between two products both called "Achilles" (search [5] noise) and chose to focus on the getachilles.ai manufacturing service, grounding the final answer in the correct domain's three fetched pages rather than being derailed by search results.
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