Ami vs Hyper: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Ami and Hyper — 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.
Hyper
Hyper
A company knowledge layer that learns from Docs, Slack, Email and Calendar to power smarter, context-aware AI across teams.
Key features
- Unified Knowledge Ingestion: Continuously imports and indexes data from Docs, Slack, Email, and Calendar to build a central, searchable company knowledge graph.
- Contextual AI Plug-ins: Provides an interface and connectors so teams can inject company-specific context into external or internal AI models, improving accuracy and relevance of responses.
- Persistent Institutional Memory: Retains historical context across conversations and workflows so the system remembers past decisions, preferences, and policies without manual re-entry.
- Real-time Sync and Updates: Keeps ingested sources up to date with near real-time synchronization so answers reflect the latest documents, messages, and schedule changes.
- Access Controls & Security: Enables role-based access and privacy controls to ensure sensitive documents and communications are only used where permitted.
- Searchable Knowledge Retrieval: Offers semantic search and retrieval of relevant docs, messages, and calendar events to surface precise context for queries and automations.
- Workflow Automation: Leverages stored knowledge to trigger or assist with routine tasks (e.g., follow-ups, meeting summaries) and reduce manual work.
- Integration Framework: Supports connectors and APIs to integrate with common productivity tools and plug the company brain into existing AI assistants or platforms.
- Ingests and learns from Docs, Slack, Email and Calendar
- Creates a centralized, searchable company knowledge layer
- Integrates/"plugs into" existing AI systems to provide context and memory
- Context enrichment for downstream AI responses and workflows
- Connectors to common collaboration sources (Docs, Slack, Email, Calendar)
Best for
- Onboarding Acceleration: New hires query the company brain to get accurate, contextual answers about processes, past decisions, and team norms without repeatedly asking colleagues.
- Customer Support Enablement: Support agents retrieve up-to-date product docs, past tickets, and policy notes to craft faster, consistent responses to customers.
- Meeting Summaries & Action Items: Automatically summarize calendar events and linked documents, then surface follow-ups and owners based on historical context.
- Internal Knowledge Discovery: Employees search across Slack, emails, and docs to find precedents, design decisions, or technical notes relevant to current projects.
- Automated Follow-ups: Use contextual knowledge to draft or schedule follow-up emails and tasks after meetings, ensuring continuity and reducing manual tracking.
- Compliance & Audit Readiness: Aggregate and index communications and documents to simplify internal audits and demonstrate policy adherence with searchable records.
- Developer and Product Support: Engineers and PMs query past architecture decisions, bug histories, and release notes to speed troubleshooting and planning.
- Provide company-specific context to LLMs and AI assistants
- Centralized knowledge retrieval and enterprise search across Docs, Slack, Email and Calendar
- Faster onboarding by surfacing institutional knowledge
- Automated summarization and context-aware drafting for email and meetings
- Enriching customer-support or internal automation agents with up-to-date company info