Your Tools See Errors. SignalManager Sees Revenue Impact.
Every error spike, payment failure, and conversion drop is a signal. SignalManager AI connects them across Sentry, Stripe, Datadog, GitHub, and more — then tells your team exactly what to fix first so every decision drives revenue.
Ingests signals from the tools you already use
97%
of alerts are noise — only 3% need action
Source: PagerDuty State of Digital Operations
$9K/min
average cost of undetected downtime
Source: Gartner IT Downtime Report
50%
of sprint time lost to firefighting bugs
Source: Stripe Developer Coefficient Report
62%
of customers never return after a failed payment
Source: Baymard Institute UX Research
Built for Teams That Ship Revenue
Every role gets the context they need to make better decisions, faster
Engineering Leaders
“My team spent two sprints on a P1 that affected 12 users. The payment bug quietly churning hundreds went unnoticed.”
- Prioritize by revenue impact, not severity labels
- Justify engineering investment with real revenue data
- See which technical work has the highest revenue upside
Developers
“I had 47 alerts open across Sentry, Datadog, and PagerDuty. Half were duplicates. I had no idea which one actually mattered.”
- One view across all tools — no more tab-hopping
- Full context in every ticket — what changed and how to fix it
- Build custom connectors with the TypeScript SDK
Product & Revenue Teams
“Conversion dropped 15% last quarter. Engineering said nothing was broken. Turns out three silent bugs were eroding trust.”
- See how technical health drives conversion and retention
- Put a dollar figure on every issue
- Align engineering and revenue around shared data
The Signals That Move Your Business Are Hiding in Plain Sight
Every one of these is a revenue opportunity your team could act on — if they knew about it in time.
Tracking & Config Drift
Analytics events stop firing, A/B tests misconfigure, integrations drift. Teams that catch these early protect conversion rates and keep growth on track.
Payment & Activation Gaps
When a webhook fails, customers pay but don’t get activated. Catching this fast means higher activation rates, fewer refunds, and stronger first impressions.
Leading Indicators Are Gold
Auth rate dips, retry spikes, and geo-specific shifts happen days before revenue moves. Teams that act on these leading signals stay ahead of the curve and protect growth.
UX Quality = Retention
Subtle data inconsistencies and UI bugs erode trust quietly. Teams that surface and fix these fast see measurably better retention and lower churn.
How It Works
Four steps from raw events to revenue-driving decisions
Connect
Connectors ingest every event from Sentry, Stripe, PostHog, Datadog, GitHub, and more. Connect once and never miss a signal that could impact your business.
Correlate
AI connects the dots across sources. A retry spike + a geo-specific auth drop + a conversion dip aren’t three separate alerts — they’re one business-critical story.
Surface
The highest-impact signals rise to the top. Your team sees exactly what matters — ranked by business impact — so they work on what actually moves the needle.
Act
Prioritized tickets land in Jira, Linear, or GitHub Issues with full context, revenue impact, and a recommended fix — ready for your team to ship.
Disconnected tools hide your highest-impact opportunities.
Most teams have signals scattered across 5+ tools with no way to see the full picture. SignalManager AI connects everything into one platform — so AI can correlate alerts, score by revenue impact, and surface the work that actually moves the needle.
Disconnected Tools
- • Alerts scattered across 5+ tools, no full picture
- • Team guesses what to work on based on loudest alerts
- • Revenue-impacting issues sit unnoticed for days
- • No way to correlate signals across sources
SignalManager AI (Connected)
- • Every tool connected — one platform, full picture
- • AI correlates signals across all sources automatically
- • Prioritized by revenue impact — not alert volume
- • Open platform — your data, your AI model, your control
One Platform for Every Signal Source
Connect Jira, GitHub, Sentry, PagerDuty, Stripe, Datadog, Slack, and more. SignalManager AI ingests signals from across your entire stack and correlates them into a single, revenue-prioritized view.
Growing Connector Library
Connect Sentry, GitHub, Stripe, Datadog, PagerDuty, Jira, Linear, PostHog, Slack, and more. Pre-built connectors plus a TypeScript SDK for custom sources.
Cross-Source Correlation
AI connects the dots across all your tools. A Sentry spike + a Stripe refund increase + a PostHog conversion drop = one correlated business story.
Revenue Impact Scoring
Every signal cluster is scored by estimated business impact. Your team instantly knows which issue to fix first — the $50K opportunity vs. the $500 noise.
Data Sovereignty
Your signals stay on your infrastructure. Open platform with MCP + API access. Use any AI model. Full transparency. No vendor lock-in.
Connects with the tools you already use
Everything You Need to Manage Every Signal
Six capabilities that turn scattered events into revenue-driving clarity
Business Signal Correlation
See the full picture. A Sentry error spike + a Stripe refund increase + a PostHog conversion drop = one correlated story your team can act on immediately.
Leading Indicator Detection
Act on the early warnings that predict revenue movement. Auth rate dips, retry spikes, and geo-specific shifts — spotted hours before MRR feels the impact.
Revenue Impact Scoring
AI scores every signal cluster by estimated business impact. Your team instantly knows which issue to fix first — the $50K/month opportunity vs. the $500 noise.
Payment Pipeline Monitoring
Ensure every payment converts to an activated user. Spot webhook-to-entitlement gaps instantly and keep your activation rates — and revenue — on target.
Conversion Anomaly Alerts
Know within hours when trial-to-paid conversion dips, tracking breaks, or funnels degrade. Act fast, protect growth, and keep your conversion engine running.
Automated Prioritized Tickets
Every ticket lands in Jira, Linear, or GitHub with full context, revenue impact, affected segments, and a recommended fix. Your team ships faster, smarter.
Revenue Opportunities Most Teams Miss
Real scenarios where managing signals early means protecting — and growing — revenue.
Protect Conversion Revenue
A SaaS team discovered that analytics events had stopped firing and an A/B test was misconfigured for two weeks. None of it triggered alerts. With SignalManager AI, these signals are correlated and surfaced in hours. Teams that catch tracking drift and config issues early protect their conversion rates and keep tens of thousands in revenue on track every month.
Business Objective
“Detect leading indicator anomalies (like trial → paid conversion dipping) within 6 hours so we can act fast and protect MRR growth.”
- Correlates tracking loss, config drift, and integration failures
- Estimates revenue exposure per signal cluster
- Alerts hours before business metrics shift
Maximize Payment Activation
A single unreliable webhook means customers pay but don’t get activated. For growing SaaS teams, this is one of the highest-leverage fixes possible. SignalManager AI monitors your entire payment → fulfillment pipeline and flags mismatches in real-time. Teams that nail activation see higher retention, fewer refunds, and stronger MRR growth.
Business Objective
“Ensure payment → fulfillment pipeline is 99.9% correct; alert when webhook → entitlement reconciliation fails.”
- Monitors Stripe webhook → entitlement reconciliation
- Flags payment/activation mismatches in real-time
- Creates tickets before support queues fill up
Stay Ahead with Leading Signals
Revenue dashboards are lagging indicators. The smartest teams don’t wait for MRR to move — they act on the early signals. Auth success drops 8% in APAC. Retry spikes appear on a key endpoint. Traditional monitoring treats these as separate, low-priority events. SignalManager AI connects them into one business story — giving your team a head start.
Business Objective
“Surface segment-specific metric shifts as early signals so we can act before business impact materializes — and stay ahead of competitors who wait.”
- Detects segment-specific degradation (geo, plan, cohort)
- Correlates technical leading signals to business trailing metrics
- Projects revenue exposure before the impact materializes
Turn UX Quality Into Retention
A product team found that tasks were silently disappearing due to a data consistency bug. No errors. No alerts. Just slowly rising churn. Teams that catch subtle UX issues early — state inconsistencies, failed updates, vanishing data — don’t just prevent churn. They build the kind of product trust that turns users into advocates and drives organic growth.
Business Objective
“Monitor user flow errors and correlate with session abandonment — fix trust-eroding issues fast so retention stays strong and NPS keeps climbing.”
- Correlates soft errors with session abandonment patterns
- Identifies UX degradation before retention metrics slip
- Quantifies churn risk from trust-eroding bugs
The Difference Signal Management Makes
Teams that manage their signals don’t just avoid problems. They make better decisions, ship faster, and grow revenue.
Without Signal Management
- 1. Signals scattered across 5+ tools. No one sees the full picture.
- 2. Team guesses what to work on based on loudest alerts.
- 3. High-impact business issues sit unnoticed for days or weeks.
- 4. Revenue opportunities missed. Growth slows.
- 5. Reactive firefighting instead of strategic execution.
With SignalManager AI
- 1. Every signal ingested, correlated, and scored by business impact.
- 2. Team sees exactly what to prioritize — ranked by revenue upside.
- 3. Conversion and payment issues caught in hours, not weeks.
- 4. Tickets land with full context, fix recommendations, and impact data.
- 5. Faster shipping. Smarter decisions. Revenue keeps growing.
The connected signal platform is coming. Get in early.
Connect all your tools. Let AI prioritize by revenue impact. Join the waitlist to get early access, shape the product, and lock in founding member pricing before we launch.
Simple, Credit-Based Pricing
Credits cover platform processing — signal ingestion, correlation, and ticket generation. AI model costs managed separately.
Free
$0/mo
500 credits/mo
- 3 team members
- Basic connectors
- Email support
Team
$79$63/mo
5,000 credits/mo5,000 credits/mo · billed $756/yr
Save $192/yr vs. monthly
- All connectors
- 15 team members
- Email support
Growth
$199$159/mo
15,000 credits/mo15,000 credits/mo · billed $1,908/yr
Save $480/yr vs. monthly
- Unlimited members
- Smart model routing
- Priority + Slack
Enterprise $750+/mo
Unlimited credits, Intelligence Network, SSO, RBAC, dedicated CSM & custom SLA.
Frequently Asked Questions
Common questions about SignalManager AI
What is a “signal” in SignalManager AI?
A signal is any event from your technical or business systems — a Sentry error, a Stripe webhook, a PostHog conversion event, a Datadog alert, a GitHub deploy, or an auth rate metric. SignalManager AI normalizes them into a unified schema so they can be correlated across sources. A Sentry error, a Stripe refund spike, and a PostHog conversion drop within the same window might be one business incident — SignalManager AI connects those dots automatically.
How is this different from traditional monitoring?
Traditional monitoring (Datadog, PagerDuty, Sentry) catches hard signals — server down, error spike, latency threshold. Those are table stakes. SignalManager AI goes further: it ingests signals from both technical and business systems, correlates them with AI, and tells your team what to prioritize by business impact. It’s the layer between your tools and your business decisions.
What kinds of problems does SignalManager AI catch?
Conversion dips from tracking drift or A/B test misconfigs. Payment webhook failures where users pay but aren’t activated. Geo-specific auth degradation. Subtle UX bugs that quietly erode retention. These are all revenue-impacting events that traditional monitoring doesn’t flag. SignalManager AI ingests them, connects the dots, and helps your team act on the ones that matter most.
How are credits calculated?
One credit = one AI analysis operation. Ingesting signals is free. Credits are consumed when AI correlates signals, scores business impact, or generates tickets. Self-hosted users have no credit limits — you pay your AI provider directly.
Which AI models are supported?
SignalManager AI works with any OpenAI-compatible API: OpenAI (GPT-4o, GPT-4), Anthropic (Claude), local models via Ollama or vLLM, Azure OpenAI, Google Gemini, and more. You bring your own API key — no vendor lock-in.
How do MCP and the API work?
SignalManager AI gives you two ways to connect: a built-in MCP server (Model Context Protocol) and a REST API. MCP is the open standard that lets AI models connect directly to external data sources — any MCP-compatible client (Claude Desktop, custom agents, internal tools) can query your signals natively. The REST API gives you full programmatic access for custom workflows, automation, and integrations with any system. Both are first-class. You bring your own AI model, your data stays on your infrastructure, and you can switch models anytime.
Stop Drowning in Alerts. Start Driving Revenue.
One platform for every signal source. AI correlates alerts and prioritizes by revenue impact. Get early access and founding member pricing.