Clear decision guides for AI & Workflow Automation Agencies
Straight comparisons of the tools you're choosing between, honest about where each one falls short. Where we quote a benchmark, we show its source.
16 guides for AI & Workflow Automation Agencies of 1,000
Keeping Client API Keys Straight Across AI Agent Workflows
A worked example of how model provider keys leak across client workflows at an AI automation agency, and how Doppler and Vault each prevent it.
When an AI Workflow Fails Quietly, Who Gets Paged
AI and workflow automation agencies need alerts on drift and failed jobs first. Here is how incident.io and PagerDuty fit once you have something to page on.
Application Security for Agencies Building AI Workflows
How AI and workflow automation agencies weigh Snyk against GitHub Advanced Security when every build pulls in new packages and API keys fast.
Testing Agent Workflows in CI When the Output Isn't Deterministic
How AI automation agencies structure CI/CD for agent pipelines, why unit tests fall short, and what to check before shipping a client automation.
Database Infrastructure for AI Automation Agencies
AI and workflow automation agencies need vector search, job state, and predictable costs. Here's how Supabase and AWS RDS compare for that work.
Wiz vs Prisma Cloud for AI Automation Agencies and Secrets Sprawl
AI and workflow automation shops hold client API keys across dozens of integrations. Here's the real risk that decides between Wiz and Prisma Cloud.
Datadog vs New Relic for AI Agent Pipelines
Datadog vs New Relic for an AI or workflow automation agency: instrumenting token cost and latency yourself, and tracing a multi-step agent run.
SOC 2 for AI Automation Agencies: Vanta, Drata or Secureframe
SOC 2 for agencies building AI workflow automations inside client systems, and how Vanta, Drata and Secureframe fit that access model.
CrowdStrike vs SentinelOne for AI Automation Agencies
An automation agency's real risk is stored client credentials, not malware alone. Here is how CrowdStrike and SentinelOne handle that specific threat.
AWS or Google Cloud for an AI Automation Agency's Workloads
A practical runbook for AI and workflow automation agencies choosing between AWS and Google Cloud for model access, storage and client isolation.
Kong vs Apigee for Agencies Proxying AI Model Endpoints
Streaming responses, per-client spend ceilings, and token accounting break ordinary gateway assumptions. How Kong and Apigee handle proxying AI endpoints.
Kubernetes vs. ECS for Spiky AI Inference Workloads
Compare how Kubernetes and AWS ECS handle scale-to-zero, cold starts, GPU workloads, and batch scheduling for bursty AI automation and inference jobs.
Rolling Out AI Automations Safely: LaunchDarkly vs Split
AI and workflow automation agencies need a kill switch as much as a rollout plan. See how LaunchDarkly and Split compare for gating agent and prompt versions.
Backstage vs Port for a Growing Automation Runner Fleet
Automation shops build homegrown runners faster than they document them. See how to choose between Backstage and Port once that sprawl gets hard to track.
Cursor vs GitHub Copilot for Teams Building Client Automations
Automation agencies mostly write connector glue, not a monolith. Why that changes the Cursor vs Copilot call and what to check before either sees secrets.
Auth0 vs Clerk When Your Product Includes AI Agents
A step-by-step approach to choosing Auth0 or Clerk when your automation agency ships AI agents that act on behalf of human users.