Middleware GTM brain

category

market profile

• text: Cloud engineering teams need to connect infrastructure, application and user experience telemetry to diagnose incidents.
• text: Observability cost and time to resolution are explicit buying concerns in customer stories.
• text: AI-assisted incident detection and remediation is becoming part of the observability product category.

personas

• title: Site reliability engineer or DevOps engineer
  pains:

  • Investigating incidents across separate logs, metrics and traces takes too long
  • High alert volume and repetitive diagnosis increase operational load
• title: Engineering or platform leader
  pains:

  • Observability spending grows with telemetry volume
  • Long resolution times affect service reliability and engineering capacity
• title: Application developer
  pains:

  • Slow endpoints and frontend errors are difficult to trace to backend causes
  • Production debugging competes with feature delivery

icp

• text: Cloud-native software organizations running production applications and infrastructure on AWS, Azure, GCP or Kubernetes.
• text: Technology, retail, finance and gaming companies with engineering teams responsible for application reliability.
• text: Teams ranging from self-service users to enterprises requiring bring-your-own-cloud and custom retention.

message pillars

• text: Observe the full stack with an AI SRE agent.
• text: Detect and resolve issues across infrastructure and applications.
• text: Make telemetry spending more controllable.
• text: Unify observability for faster troubleshooting.

objections

• objection: Observability costs will grow unpredictably with ingest.
  response: Model expected data, session and test volumes with the pricing calculator and evaluate ingestion controls.
• objection: Can we trust AI to fix production incidents?
  response: Run a limited pilot with human review and define permissions and rollback procedures before enabling automation.
• objection: Migration from our existing monitoring stack could be disruptive.
  response: Test a representative service and telemetry sources in parallel, then compare dashboards, alerts and operational cost.

competitors

• name: Datadog
  why: Full-stack cloud observability and AI SRE alternative.
• name: New Relic
  why: Competing application and infrastructure observability platform.
• name: Dynatrace
  why: Enterprise observability and operations platform.
• name: Grafana Labs
  why: Competes for dashboards, metrics, logs and traces.

keywords

• full stack observability
• AI SRE agent
• cloud monitoring platform
• application performance monitoring
• Datadog alternative
• logs metrics traces
• Kubernetes observability
• observability pricing

voice

• Technical and direct
• Outcome and cost-conscious
• Confident about automation

signals

• text: Observability spend is increasing with telemetry volume or contract renewal is approaching.
• text: Engineering teams are consolidating logs, APM and infrastructure monitoring.
• text: An SRE organization is evaluating incident investigation or remediation automation.

stack

• AWS
• Microsoft Azure
• Google Cloud
• Kubernetes

hiring

• Senior Software Engineer (Backend), Ahmedabad
• Senior Sales Engineer, Ahmedabad
• Senior Growth Marketer, Ahmedabad
• Technical Solution Engineer, Ahmedabad
• Growth Engineer - GTM, Ahmedabad

pricing

motion

channels

• SEO
• Documentation
• Free self-service
• Customer stories
• Slack community
• Webinars and events

confidence

Founders

• name: Laduram Vishnoi
  title: Founder
  role: Founder
  bio: Founder & CEO at Middleware. Ex-founder of Acquire.io, a customer engagement platform, I took the company from just myself to 200 people and raised $57m in venture capital until the Series B round. Side angel investor and advisor. Born in a small town in India called Jodhpur, grew up in London and living in San Francisco since 2016.