Altair

Research agent. Altair gathers, analyses, and synthesises information from multiple sources — your internal knowledge graph, the web, analytics platforms, user research repositories, and usability tests — and returns structured findings with evidence citations.

What Altair Does

Where most research ends with a Notion page nobody reads, Altair ends with atoms in your knowledge graph. Every finding is saved as a typed atom (DATA, LEARNING, or DECISION), linked to the task or goal that triggered the research, and immediately searchable by your whole team.

Internal research — searches atoms, documents, and prior agent learnings in your workspace for existing knowledge before going external
Web research — autonomous Google search with multi-page synthesis; returns a structured report, not a list of links
Google Analytics — queries GA4 metrics, surfaces traffic and conversion patterns, and saves findings as DATA atoms
User research synthesis — processes interview transcripts, usability recordings, and survey exports into LEARNING atoms with source quotes
Competitive intelligence — monitors competitor public signals and synthesises into LEARNING atoms with timestamps

Use Cases

Task type	What Altair produces
Pre-feature research	Gap analysis — what's known, what's missing, what the team decided last time
Competitive landscape	Structured comparison with source citations; saves as LEARNING atoms
Analytics investigation	DATA atoms from GA4 or Mixpanel queries, flagged for human review
User research synthesis	LEARNING atoms with verbatim source quotes from transcripts or recordings
Best-practice audit	Structured report with ranked recommendations and evidence

How It Works

Task assignment — assign Altair to a task with a clear research question or objective in the description.
Internal-first — Altair searches existing atoms and documents in your workspace before going external. If the answer is already there, it surfaces it immediately.
External research — if the internal graph is insufficient, Altair queries web sources, analytics APIs, or provided documents.
Synthesis — findings are consolidated, deduplicated, and classified into atom types.
Knowledge save — atoms are created in your knowledge graph with source citations, confidence scores, and links to the triggering task.
Report — Altair posts a structured summary to the task comments and marks the task for human review.

Writing Good Research Tasks

Altair performs best when the task has a specific, answerable question — not an open-ended topic.

Good	Too vague
"What are the top 3 reasons enterprise users abandon the setup flow? Use our GA4 data + any user research atoms in the workspace."	"Research our onboarding"
"Compare Notion AI, Coda, and Linear's AI agent features as of May 2026. Focus on task automation, not writing assistance."	"Research competitors"
"Find any prior decisions in the workspace about auth token expiry. If none, research industry standards for B2B SaaS JWT TTLs."	"Research auth best practices"

Assigning Work to Altair

// Create a research task
const researchTask = await task({
  statement: "Research why enterprise users abandon the setup flow",
  parentId: "epic_onboarding_q2",
  description: "Use GA4 funnel data + any usability test atoms in workspace. Deliver: top 3 reasons with evidence, prioritised by impact.",
  acceptanceCriteria: "At least 3 DATA or LEARNING atoms saved. Each has a source quote or metric citation."
});

await task({
  action: "assign",
  taskId: researchTask.id,
  agentId: "mmp-altair"
});

Access

Altair is in alpha. Available to invited teams on Pro and Enterprise plans. Contact hello@momentalos.com to get access.