Ami vs Replit Agent 3: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Ami and Replit Agent 3 — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Ami
AiSDR
AI GTM agent that picks the audience, writes and launches outbound campaigns, reads the results and fixes what stops working.
Key features
- Autonomous Campaign Loop: Ami picks the target audience, builds and launches the campaign, reads what comes back and changes what is not working, so each campaign sharpens the next without a human restarting the cycle.
- Baked-In GTM Experience: Arrives with 27 industry playbooks and the lessons of 17,150 prior AiSDR campaigns and 19,501 meetings, so a first campaign launches with patterns other teams paid to learn.
- Signal-Triggered Outreach: Watches hiring, funding and job-change signals and acts at the moment they happen rather than months later.
- Performance Triage: When response rates slip, Ami digs into audience, message and sequence to pinpoint what is breaking and proposes fixes before the budget is spent — flagging, for example, a positive response rate under 1% after 21+ days.
- Omnichannel Sequences: Configurable sequences combining email via Gmail or Outlook, LinkedIn connection requests, DMs and InMail, and AI call steps through the Aircall dialer with scripts and automated follow-ups.
- Deep Per-Lead Personalization: Researches the top three most relevant data points per lead and personalizes from ICP data, activity, LinkedIn data and HubSpot properties.
- Native CRM Sync: Two-way HubSpot sync on every plan and two-way Salesforce sync on higher tiers, with AI research and monitoring running over that CRM data.
- Review Mode: Campaigns and Ami's proposed corrections stay drafts until approved, so the agent's autonomy is opt-in rather than assumed.
Best for
- Founder-Led Outbound: A solo founder builds pipeline without hiring an SDR, starting self-serve with no sales call required.
- Rescuing Stalled Campaigns: A revenue team catches a dying sequence early when Ami flags a collapsing positive-response rate and rewrites the audience or message.
- Replacing Outbound Agencies: A company that has paid outside firms without results brings the motion in-house under one agent.
- Warm-Signal Prospecting: A sales team reaches buyers right after a funding round, a relevant hire or a job change instead of cold-listing an industry.
- CRM-Grounded Targeting: A HubSpot or Salesforce team has outreach built from and logged back into existing CRM data rather than a disconnected tool.
- Multichannel Follow-Up: A team runs email, LinkedIn and dialer touches in a single sequence with replies handled in 5-10 minutes or in co-pilot mode.
Replit Agent 3
Replit
Autonomous coding agent that builds, tests, and fixes apps automatically with long runtimes and workspace integrations.
Key features
- Autonomous App Construction: Builds full applications from project context and instructions, orchestrating multiple development steps (scaffolding, dependency installation, and initial code generation) without continuous human input.
- Automated Testing and Fixing: Runs test suites, detects failing tests or runtime errors, and iteratively applies fixes to source code until tests pass or a defined stopping condition is met.
- Extended Runtime Sessions: Supports long-lived agent runs (advertised up to 200 minutes) to handle multi-step workflows, long-running builds, or extensive debugging sessions that shorter agents cannot complete.
- Tool and Workspace Integrations: Connects with external collaboration tools such as Slack and Notion to post results, receive triggers, and integrate agent activity into team workflows and documentation.
- Sandboxed Code Execution: Leverages Replit's code-exec/eval infrastructure to execute generated Python (and other) code in ephemeral, unprivileged containers for numerical reasoning, testing, and validation.
- Multi-step Orchestration and State Handling: Manages sequential tasks, preserves context across steps, and can coordinate edits, tests, and deployments across a project repository.
- Notification and Reporting: Produces actionable reports and sends notifications to integrated tools or channels about build status, test results, and applied fixes.
- Autonomous build, test, fix, and redeploy loop
- Agent-of-agents: can generate other agents/automations
- Integrations with Slack, Notion and other tools
- Extended runtime (advertised 200min runtime on the product page)
- Metered usage via Replit credits and usage-based billing
- Deployable agents and testing workflows
- Automatic build, test, and fix cycles for applications
- Extended runtime for agents (advertised 200 minute runtime)
- Higher autonomy compared to prior versions (advertised 10x more autonomous)
- Integrations with external tools and services (examples: Slack, Notion)
- Designed to work with Replit code-exec APIs and ephemeral execution containers
- Optimized for agents to evaluate generated Python code and perform numerical reasoning
Best for
- Automated CI-like Workflows: Continuously run test suites, reproduce failing tests, and automatically propose or apply fixes, reducing manual triage time for developers.
- Bug Triage and Repair: Given a failing test or bug report, reproduce the issue in a sandbox, identify root causes, and generate patches or pull requests that fix the problem.
- Long-running Feature Implementation: Implement multi-step features that require iterative development, testing, and dependency management within a single extended agent run.
- Integration-driven Notifications: Monitor repository activity or CI signals and post detailed updates, diagnostics, and suggested fixes into Slack or Notion for team visibility and tracking.
- Prototype to Deployment: Rapidly scaffold prototypes, run end-to-end tests, and assist in deploying simple apps or demos using Replit's hosting capabilities.
- Interactive Code Evaluation: Execute generated scripts or numerical reasoning code in ephemeral containers to validate outputs and adjust generation strategies based on results.
- Automated feature development and iterative bug-fixing
- Creating autonomous bots or agents for internal workflows
- Automating testing and CI-like workflows for small apps
- Rapid prototyping and deploying small services with integrations
- Team collaboration where agents assist coding and review
- Automated end-to-end app development tasks (build, test, fix) driven by natural-language prompts
- Running longer-running agent tasks such as extended debugging or integration workflows
- Evaluating generated code snippets or numerical reasoning via Replit's code-exec interfaces
- Integrating development workflows with collaboration tools (Slack, Notion) for notifications or orchestration
- Using ephemeral sandboxed containers for safe execution of agent-generated code