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AI Agent Infrastructure

Know before your client does.

The control plane for AI agencies. Ship agents with real identities, live observability, and auditable workflows — so failures are caught, logged, and explained before a client ever opens a ticket.

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✉   NEW — GIVE YOUR AGENT AN EMAIL

Your agent has an inbox. Claim its address.

Type a name. Get youragent@agentgateway.com in 60 seconds. Your clients email it like a colleague — it runs the workflow and replies. Every thread logged, metered, auditable.

@agentgateway.com

Free tier includes 1 agent email. No credit card.

  • 📧 Real email address — not a webhook
  • 📎 Attachments supported — PDFs, CSVs, images
  • 🔒 Every thread logged and metered

Built for agencies running production AI agents across GPT, Claude, Gemini, and open-source models.

🔒 app.agentgateway.com ALL SYSTEMS OPERATIONAL

Overview

Last 24 hours · Acme Agency

LIVE
Uptime (30d) 99.98% ▲ 0.04% vs last period
Calls today 48,213 ▲ 12.4% WoW
Hours saved 342h this month, 12 agents
Live Feed LIVE
14:02:31 200 intake@acme parsed invoice → HubSpot deal created 842ms
14:02:24 429 router rate limit OpenAI → failover to Claude 118ms
14:02:15 200 qa-writer@globex draft reply → thread #8812 1.2s

Plays nicely with the tools your agents already use

The cost of not knowing

The client who emails you first is the client you’re about to lose.

An untracked failure isn’t a bug. It’s an invoice you can’t defend.

Silence in your monitoring is not good news. It’s the absence of news.

AgentGateway sits between your agents and every client-facing moment that matters. You see it before they do. Every time.

See how it works →
The problem

Flying blind is costing you clients.

Every agency running AI agents hits the same wall: prompts drift, models rate-limit, tools 500 — and the first signal is a message from the client. By then trust is already leaking.

🔍

No identity

Your agent is a webhook behind a Zap. Clients can’t email it, can’t cc it, can’t file a ticket to it. It’s invisible until it breaks.

73% of agent failures are reported by clients first
📊

No observability

Logs live in four different dashboards. When something breaks at 11pm, you’re grepping stdout across Make, n8n, OpenAI, and Stripe to figure out what happened.

Avg time to diagnose: 2.4 hours
📜

No proof

When a client asks “what did the agent actually do?” the honest answer is: we’ll have to check. That answer costs retention.

1 in 5 agency contracts churn after a silent failure
Platform

Seven capabilities. One gateway.

Everything an agency needs to run agents in production — from identity to audit.

01 · Real-Time Failure Alerts

Catch it before the client does.

Detect prompt drift, rate limits, tool 500s, and anomaly spikes in under 60 seconds. Email alerts per client, per severity.

  • Per-client SLA thresholds with auto-escalation
  • Anomaly detection on run volume, latency, and cost
  • Auto-pause on cascading failures (circuit breaker)
⚠ HIGH SEVERITY 2m 14s ago

Intake agent missing required field customer_id

Client: Acme Corp Model: gpt-4o Impact: 3 of 47 runs
→ Pattern match: prompt_drift.v12
→ First seen: Apr 14, 09:02 UTC
→ Root cause: template refactor
✉ ops@acme ✉ oncall@acme ✉ billing@acme
Open run Auto-fix with AI
02 · Failure Pattern Recognition Engine

Every failure, classified and trended.

An always-on engine that clusters failures into patterns, scores them against your rubric, and tells you which one is actually costing you retention.

  • LLM-judge + human-in-the-loop scoring
  • A/B prompt performance tracking across models
  • 7-day pattern trend by agent, client, and root cause
Failure patterns · 7-day
2,412 runs analyzed
Prompt drift — missing fieldspattern.prompt_drift.v12
24 ▲
Rate limit — OpenAI tierpattern.rate_limit.openai
18
Tool 500 — HubSpot webhookpattern.tool.hubspot
9 ▼
Passed rubric (accuracy ≥ 0.9)scorer.rubric.accuracy
2,361
Tone compliancescorer.rubric.tone
2,124
03 · Immutable Audit Trail

Signed, append-only, exportable.

Every agent decision — every prompt, tool call, token, cost — written to a cryptographically signed chain. Export per client, per quarter, per compliance review.

  • HMAC-SHA256 hash chain — tamper-evident by construction
  • 7-year retention on Enterprise plan
  • Export per client, per quarter, per compliance review
audit.log · acme-corp APPEND-ONLY
14:03:09intake email.received msg_id=8811#a91f..c4
14:03:09intake llm.classify model=claude-3.7 cost=$0.003#b12e..0a
14:03:10intake vault.read key=HUBSPOT_API_KEY#c08d..1f
14:03:10intake hubspot.deal.create id=2941#d3ab..9e
14:03:11intake email.reply subject="Re: RFP"#e4f0..22
14:03:12scorer rubric.grade accuracy=0.94 tone=0.91#f771..b8
14:03:13gateway chain.commit block=84,921#0a1c..d3
block #84,921 · HMAC-SHA256 chain ✔ chain valid
04 · White-Label Client Reports

Monthly PDF, auto-branded, auto-sent.

Your logo, your tone, your client. Every month, a polished PDF lands in their inbox with the numbers that keep them on retainer.

  • Drag-in logo → branded for every client
  • Natural-language narrative from actual run data
  • Scheduled delivery — first of the month, 9am local
M&F

Marshall & Fitch

Agent Activity Report

PeriodApril 2026
12,480Agent actions
99.4%Success rate
342hHours saved

This month your intake agent handled 12,480 actions with a 99.4% success rate. Three incidents were auto-resolved within SLA. Model mix: 72% Claude, 28% GPT-4o. Top workflow: RFP intake → HubSpot → draft reply (4,812 runs).

Generated by AgentGateway · signed chain #84,921 marshallandfitch.com
05 · Agent Email Identity

Your agent has an inbox.

Every agent gets a real, addressable email — not a webhook. Clients email it, cc it, attach files, loop in teammates. The agent runs the workflow and replies inline.

  • Unlimited addresses on Pro + Enterprise plans
  • Custom domains on Agency + Pro + Enterprise — send from @yourclient.com
  • Auto-threaded replies, human-cc ready, always logged
06 · AI Troubleshooting Agent

A meta-agent that debugs itself.

Point it at a failing run. It reproduces the issue, isolates the root cause, proposes a patch, and stages the rollout. No more grepping stdout at midnight.

  • Auto-reproducible failing runs in a sandboxed replay
  • Suggested prompt + config diffs, human-approved
  • One-click rollback on regressions (7-day window)
Troubleshoot run_8812
claude-3.7 · 4 steps
1
Reproduce done

Re-ran failing input in shadow mode — same error: missing customer_id in 3/3 replays.

2
Isolate done

Bisected against prompt history. Regression introduced in template intake.v12 (Apr 14, commit a91f).

3
Propose patch in review

Restored customer_id field to the return JSON schema. Tested on 12 shadow runs: 100% pass.

4
Roll out

Staged canary at 5% → 25% → 100% over 30 minutes. Auto-rollback on p95 regression.

07 · API & Login Vault

One vault. Every client. Zero leaks.

Every API key, every login, every OAuth token — encrypted, scoped, and rotated on schedule. Your agents pull credentials; your team never sees them.

  • AES-256 at rest, scoped per client, audit-logged on access
  • Auto-rotation schedules + break-glass recovery
Credential Vault
AES-256 · scoped per client
  • 🔑 HUBSPOT_API_KEY acme-corp •••••e41f
  • 🔑 STRIPE_SECRET globex •••••d22b
  • 🔑 OPENAI_API_KEY shared •••••9a1c
  • 🔑 SLACK_BOT_TOKEN acme-corp •••••7f84
  • 🔑 SALESFORCE_OAUTH initech rotated 2d
14 credentials · 3 clients Next rotation in 6d
How it works

Every call. Every step. Every dollar.

One proxy in front of every model and every tool — logged, scored, routed, and billed before anything hits the provider.

In

Client Email

Inbound from acme@agentgateway.com

emailwebhookAPI
→
Control plane

AgentGateway Proxy

Authenticate · route · score · log · meter

AuthRouterScorerAuditVault
→
Out

APIs & Tools

Models and systems your agents already use

OpenAIClaudeGeminiStripeHubSpot
100% Runs logged
0 SDK Drop-in proxy
MCP Gateway Layer

One endpoint. Every framework.

Plug any agent framework into AgentGateway. The MCP layer multiplexes models, tools, and credentials — so you can swap stacks without touching your agents.

LangChain
LangGraph
LlamaIndex
CrewAI
Make
n8n
AutoGen
↓ ↓ ↓
AgentGateway MCP Layer
↓ ↓ ↓
OpenAI GPT-4o Claude 3.7 Sonnet Gemini 1.5 Mistral Large Llama 3.1 + 50 tools
ROI

Price it out in 30 seconds.

Move the sliders. See what observability pays back.

Hours reclaimed / month32
Eng cost saved / month$4,800
Client retention lift+8%
Net ROI / year$52,800
Start free — keep the math
“

We ran 40 agents across 12 clients with zero visibility. One week after switching to AgentGateway, I caught a prompt-drift regression at 3am — before it hit a single client inbox. That one alert paid for the year.

DM
Dani Morales Founder, Relay Works · AI agency, 14 seats
Pricing

Pay for the rails. Earn on the runs.

Low monthly covers infrastructure. The economics live in per-run pricing — built to give agencies margin on every run, and to compensate the SaaS platforms your agents consume. Every party in the workflow gets paid. Including you.

Free

On the rails

$0/ mo

Ship one agent. See the infrastructure work.

  • 1 agent email
  • 1,000 runs / mo included
  • 7-day log retention
  • Community support
  • No overage (upgrade to go live with clients)
Start free

Start billing clients through AgentGateway from $9/mo.

Starter

First paid client

$9/ mo

For the agency running one client workflow.

  • 3 agent emails
  • 10,000 runs / mo included
  • 30-day log retention
  • White-label PDF reports (your logo, your brand)
  • Client usage invoice — billing-ready PDF, white-labeled with your logo
  • Email support
  • Basic email alerts
Per-run overage: $0.02
Start Starter
Most popular Launch pricing — 50% off

Agency

Multi-client

$29 / mo $59

The tier built for agencies billing multiple clients through one control plane.

  • 25 agent emails (custom domains — @yourclient.com)
  • 50,000 runs / mo included
  • 90-day log retention
  • White-label PDF reports (your logo, your brand)
  • Client usage invoice — billing-ready PDF, white-labeled with your logo
  • Client read-only dashboards
  • Priority support (4h SLA)
  • Email alert routing per client
Per-run overage: $0.02
Start Agency trial

Typical agency economics work out to ~67% margin on the rails themselves.

Pro

Scaling

$49/ mo

For agencies running heavy volume across many clients.

  • 100 agent emails (custom domains)
  • 200,000 runs / mo included
  • 1-year log retention
  • Client usage invoice — white-labeled PDF with custom line items
  • AI Troubleshoot Agent (auto-diagnose + auto-fix)
  • Failure pattern recognition engine
  • Custom SLA (99.95%)
  • Solution architect included
Per-run overage: $0.015 · volume discount on the rails
Start Pro

Scale on the rails. The more you run, the less each run costs — and the more the economics compound for every agency in the network.

Enterprise

Regulated / at scale

Custom

Hit a call ceiling on a connected SaaS or CRM? We negotiate with the platform on your behalf — volume pricing, dedicated rate limits, compliance terms. You get the headroom. They get the commitment. We broker the middle.

  • Unlimited emails & runs
  • Negotiated per-run rates
  • 7-year signed audit chain
  • Compliance export bundles on request
  • Client usage invoice — fully custom PDF, negotiated line items (Stripe / QuickBooks / FreshBooks export on roadmap)
  • VPC / on-prem deployment
  • Dedicated success engineer
  • 99.99% SLA
Talk to sales
⚙   The rails model

Your monthly isn’t the price. The runs are.

Monthly tiers cover infrastructure — servers, storage, compliance, the audit chain that makes this work. The real economics live in per-run pricing, structured as a three-way flow: agencies earn margin on every run, AgentGateway takes a thin cut on the rails, and the SaaS platforms your agents consume receive the majority of per-run revenue — offsetting the per-seat contracts AI agents replace. As more SaaS partners integrate, per-run economics improve for every agency on the rails.

  • ⚙ Low monthly, no budget meeting
  • 📊 Per-run cost is metered, auditable, and billable
  • 🤝 SaaS partners get paid for the value their APIs provide

What counts as a call

Every API request proxied through AgentGateway, every inbound email that triggers a workflow, and every MCP tool invocation (Phase 4).

Overage rates

TierOverage rate
FreeNot available
Starter$0.02 / run
Agency$0.02 / run
Pro$0.015 / run
EnterpriseNegotiated

Client billing economics

Your client pays for what the agent does. You add your margin. AgentGateway is the infrastructure line item that proves the work happened — and the SaaS platforms behind your agent’s APIs get paid for the value they provide.

Example: 10,000 overage runs on Agency tier = $200 cost to you.
Bill at $0.06/run = $600 client revenue.
$400 margin on infrastructure your client can see, measure, and defend.

We pay SaaS platforms for the seats AI agents replace.

For the first 24 months, the majority of per-run revenue flows directly to the SaaS and CRM partners whose APIs your agents consume. This isn’t a gesture — it’s the math that makes the agent economy sustainable for everyone in it.

SaaS / CRM Partners

70%
of per-run revenue

They receive 70% of per-run revenue on their endpoints — compensation for the per-seat contracts their platform loses as AI agents replace human users. At typical Agency-tier volumes, that’s meaningful revenue against real seat erosion. AgentGateway makes their API commercially viable in the agent era.

Automation Agencies

Margin on every run
metered + billable

You get metered, observable, billable infrastructure with a certified partner program behind it. Every run is a line item. Every line item is proof. You bill per-run costs to clients with margin, and the SaaS platforms you depend on stay in business — which means your stack stays in business.

AgentGateway

Thin cut
on the rails

This is a movement, not a markup. The more API calls your agents run end-to-end through real, metered, billable infrastructure, the more the whole agent economy becomes something real — for you, for the SaaS partners behind the APIs, and for the clients paying for work that can finally be proven. We built the pricing to reward the agencies that show up early and build in volume. Every call you run through AgentGateway is a vote for what comes next.

TierRevenue to partner
Starter70%
Agency70%
Pro70%
EnterpriseNegotiated (70–90%)

“The agencies that run the most calls through this in 2026 are the ones defining what agent infrastructure looks like in 2028.”

Why AgentGateway

The shortest path from “it works” to “we can prove it.”

Point solutions give you a slice. AgentGateway gives you the control plane.

Capability AgentGateway Datadog LangSmith Make Zapier
Agent email identity ✓ Built-in — — — —
Real-time failure alerts ✓ Per-client SLA ✓ Generic Basic Basic Basic
Signed immutable audit trail ✓ 7-year 30-day 30-day — —
White-label client reports ✓ Automated PDF — — — —
Client usage invoice ✓ Billing-ready PDF — — — —
Multi-model MCP routing ✓ Native — SDK only — —
Credential vault ✓ Per-client scoped — — Connections Connections
AI troubleshoot agent ✓ Auto-diff — — — —
Pattern recognition / scoring ✓ LLM-judge APM only Evals — —
Time to first agent in prod ~1 hour ~1 week ~3 days ~1 day ~1 day
Built for AI agencies ✓ Purpose-built Infra monitoring LLM devs Automations Automations

Billing-ready PDF. Drop into your own invoicing system for collection.

About

We’re building the reliability layer for the agentic future.

AI agents are replacing human workflows faster than the infrastructure beneath them was built to handle. Agents run 24/7 across dozens of APIs, touch production data in real time, and make decisions that cost their operators money, clients, and reputation when they fail silently. The tooling most agencies use to monitor, meter, and audit them was designed for a world of human users clicking buttons. That world is gone.

AgentGateway exists because the three parties who will shape the agent economy — automation agencies, the businesses they serve, and the SaaS platforms whose APIs make the work possible — all need the same thing: a trustworthy layer in the middle. One that catches failures before clients notice. One that produces audit trails regulated industries can actually use. One that meters every call so the economics are transparent for everyone in the chain.

We built AgentGateway so all three win.

Agencies win

by keeping clients longer, billing for provable work, and operating with the same visibility enterprise infrastructure teams have had for a decade.

Businesses win

by paying for automation they can verify, with audit trails their legal and compliance teams accept, and transparency they can show their board.

SaaS platforms win

by getting fairly compensated as AI agents replace the per-seat contracts their industry was built on — turning an existential threat into a new revenue line.

This is the thesis. The agent economy only works if everyone in the workflow gets paid, sees what’s happening, and can prove the work was done. No winners-and-losers. No one left behind as the rails get built.

We’re looking for the agencies and technology companies who see where this is going. Who don’t want to watch the agent era happen to them — who want to help build the infrastructure that makes it fair, reliable, and accountable. The companies that get on the rails early don’t just benefit from them. They help define what the rails are.

If you’re building in the agent economy — as an agency, a SaaS platform, a technology partner, or a business deploying agents at scale — we’d like to talk.

Partner with us → Get on the rails →

Know before your client does.

Free tier. No credit card. Your first agent inbox in 60 seconds.

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All systems operational