Atlas Synapse is the monitoring console that watches your AI agents the way HR watches employees. Performance reviews, incident reports, real dollar ROI. In plain English, for the person who buys AI, not the person who builds it.
Founded by alumni from
Sarah Chen
Senior Designer
Performance
92%
Last review
Q1 2026
Incidents (90d)
0
Comp
$118,000 / yr
Reviewed quarterly. HR file maintained by your ops team.
Client Intake Bot
Customer Service Agent
Performance
91%
Last review
This week
Incidents (90d)
3
Comp
$182 / mo
Reviewed daily. HR file maintained by Atlas.
Same questions. Same scorecards. New kind of employee.
Companies are pouring money into AI agents. Nobody is checking if they actually work.
of AI projects show zero measurable return after deployment
of agent-style AI initiatives expected to fail by 2027
monitoring tools exist, all built for engineers, none for business owners
Your AI agent told a client the wrong refund window. Your legal bot cited a case that doesn't exist. Your sales assistant quoted a price that expired last quarter.
Nobody flagged any of it, because nobody was watching.
The market reality
The AI agent market is $7.6B today, growing to $47B by 2030. The tools to monitor it are all built for engineers. These aren't edge cases. They're what happens when AI runs without oversight.
Every AI agent produces a stream of raw data no business owner was ever meant to read. Atlas turns that stream into one sentence: what happened, what to do, what we already fixed.
From the moment you connect us, Atlas captures every prompt, response, tool call, and decision, in real time, across every agent, every integration, every model.
Every interaction runs through an evaluation layer: factual accuracy, policy match, cost profile, hallucination risk. The output is a plain-English score you can act on.
A failed check once is an incident. Twice is a pattern. Atlas turns patterns into guardrails, applied automatically to every future query, with no developer required.
Cross-check legal citations vs Westlaw
Legal Research · 47 hits/wk
Flag cost-per-query above $0.18
All agents · 12 hits/wk
Block expired-pricing quotes
Billing Bot · 3 hits/wk
Escalate >2 client reschedules
Scheduler · 8 hits/wk
Connect your agents once. Atlas watches them forever. When something breaks, you'll know before your client does.
Connect your AI tools through the integrations you already use. Zapier, Make, n8n, direct API. No code. No developer. Events start flowing in minutes.
We run every AI interaction through Atlas' evaluation layer: fact-checking, policy matching, cost analysis, hallucination scoring. All before you ever need to look.
“Find precedent for tenant-habitability claim in California small-claims court, specifically around mold disclosure.”
“Primary precedent is Smith v. Jones (Cal. 2023), which established a five-factor disclosure test…”
Factual accuracy
Cited case not found in Westlaw DB
Policy compliance
No PII or confidential terms
Tone consistency
Matches brand voice profile
Cost efficiency
2,847 tokens, above avg for this query
The moment a check fails, we tell you what happened in plain English: which agent, which client, which action to take, and whether we already applied a guardrail.
Critical incident
inc_4f82d1 · opened 2:14 PM · Legal Research Agent
Your Legal Research Agent cited a court case that does not exist in any legal database. It was hallucinated. The response also cost 38% more than a typical query for this agent.
Client [REDACTED] received this answer at 2:14 PM. No documents filed yet.
Contact the client directly.
Retract the citation. Offer corrected research.
No documents filed yet · No public citation
Legal Research Agent will now cross-check every case citation against Westlaw before responding. Applied to all future queries.
Every other monitoring tool speaks code. We speak business.
PLAIN-ENGLISH TRANSLATION
Same data. One is for engineers. One is for you.
BUSINESS ROI, NOT TOKEN COSTS
AI tools charge by 'tokens', a unit most business owners have never heard of. We convert that into actual dollars and actual ROI.
daily cost (7d, $/day)
Token counts don't pay the bills. ROI does.
SILENT FAILURE DETECTION
⚠ P3: Hallucination detected
Agent: legal_research_v2
Type: ungrounded_citation
Assigned: backlog
ETA: next sprint
Customer notified: no
Most tools tell your tech team. We tell you, immediately, so you can act before the client notices.
This is the live console. Agent overview, live activity feed, real-dollar ROI, open incidents. Watch the right side: incident toasts pop in as they fire.
Agents online
5
all responding
Open incidents
2
1 critical
Prevented loss
$38,412
this month
Spend today
$1.59 / qry
12% under target
Customer service
Knowledge agent
Calendar bot
Pricing agent
Contracts
Legal Research Agent
Hallucinated case citation. 1 client affected.
Billing Bot
Expired Q1 pricing quoted. 3x this week.
Each number ticks in real time. No screenshots. No mock data. This is the product surface.
What you see when you log in
Every morning. One screen. What your AI did, what it cost, what broke, and what Atlas already fixed. No tech degree required.
We made a bet that the next 10 million companies running AI agents will not be staffed by AI engineers. These principles keep us honest to that bet.
Every flagged failure becomes a 2-3 sentence summary at a 10th-grade reading level. Identity stripped. Business impact first.
Example: "Your bot told a customer the return window is 60 days. Your policy says 30." Not a hallucination score.
Galileo, LangSmith, and Arize ship developer consoles. Atlas Synapse ships an HR dashboard for AI agents. Same data, business-owner surface.
Configurable by a salon owner or office manager. Zero code from the buyer.
Silent failure detection runs on every agent output, post-deploy, in production. Email arrives within 5 minutes of the incident.
Severity tiered. Deduplicated. Linked to the trace. Plain-English description in the email itself.
Join 200+ business owners already on the list. We'll tell you the moment we launch.
Join the Waitlist
No spam. Just one email when we go live.
Want hands-on early access?
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