Company Portfolio

This workflow produces company-level intelligence without assuming a report or table deliverable.

Primary Primitives

• profile-entity
• enumerate-entities
• trace-events
• trace-financings
• synthesize-evidence

Optional Primitives

• identify-analogs
• benchmark-assets
• synthesize-evidence (when LOE timing, exclusivity calendar, or label-extension opportunities shape the strategic posture and each date needs a source)

Output Contract

Return a company intelligence package that can include:

• company overview
• pipeline snapshot
• recent events
• capital posture (recent rounds, total raised in window, lead investors, financing trajectory, runway implication)
• public-market financial caveats when applicable (market cap, cash position, revenue scale)
• strategic themes
• discussion topics or diligence gaps when relevant

Aggregation Shortcuts

For the capital-trajectory and pipeline-shape views of one company, prefer aggregate_records over manually aggregating research_entity(..., aspects=["financings"]) rounds:

• Financing trajectory: aggregate_records(entity_type="financing", query="rounds for {company} by year with total value")
• Pipeline shape: aggregate_records(entity_type="drug", query="active programs for {company} by phase and indication")

Workflow Rules

• treat company/entity profiling as the baseline fact pattern, not the final synthesis
• pair aspects=["financials"] with aspects=["financings"] on research_entity for the public and private capital pictures; for VCs, corporate venture arms, and strategic investors, also pull aspects=["investments"]
• treat the related_previews.financings and related_previews.investments teaser on the default company response as a routing prompt, not as evidence; opt into the full aspect when the funding picture matters to the analysis
• on every financing row, separate the confirmed-value slice from the unconfirmed slice; never aggregate total_value_usd: null rounds into a "total raised" headline without footnoting
• augment important company, pipeline, event, and round-level claims with search_documents and read_document; the structured row is metadata, not citable evidence
• for portfolios with approved assets, surface upcoming patent expiries, biosimilar entry windows, and label-extension opportunities from primary filings via search_documents(source_types=["fda_filings", "sec_filings"]) and read_document; where no filing supports a date, record it as a gap rather than estimating it
• if host web fetch is blocked, prefer Maven-indexed document retrieval over repeated blocked fetch attempts
• when the company splits into independent evidence workstreams (pipeline, events, capital position, deals), run them in parallel with the research-assistant sub-agent, then reconcile the returned claim sets before synthesis

BD and Diligence Posture

For BD, corp dev, and acquisition-target diligence, the company portfolio should surface a runway-implication slice in addition to the pipeline picture:

• the most recent round (date, type, value, lead investor) versus the company's burn signals from aspects=["financials"]
• the financing trajectory (accelerating, flat, or aging since last round)
• investor concentration and lead-investor signal
• the comp-set position relative to peers identified through identify-analogs or enumerate-entities

A capital-thin or aging-Series-B+ recipient with active mid-stage trials is a candidate signal. A well-funded recipient with a recent strategic investor is a different posture. Make the difference visible rather than collapsing both into "company overview."

For investment-team workflows oriented around capital momentum across a space rather than one company, route to funding-landscape instead of building one company portfolio at a time.