Investing generates information — rarely understanding. PhyloAI connects founder updates, GST/MCA filings, commodity prices, hiring velocity, Amazon rankings and competitor signals into one portfolio ontology — delivering daily briefings, cross-portfolio opportunity detection and early intervention recommendations.
Founders curate board decks. PhyloAI reads what they don't show — and answers the question leadership asks between reviews: What changed since last week?
Monthly updates frame positively. External signals — filings, hiring, reviews — tell a different story weeks earlier.
Between quarterly reviews, portfolio companies can deteriorate significantly with no independent oversight.
Competitor fundraising, product launches and hiring surges affect your portfolio — but aren't tracked systematically.
Most connectors are custom-built. PhyloAI maps your portfolio ontology first, then connects the sensors that feed it.
Email updates, board reports, sentiment shifts and commitment signals parsed automatically.
GST returns, MCA filings, annual reports — anomalies and delays surfaced in days.
LinkedIn, Naukri, platform data — deceleration is often the earliest distress signal.
Google reviews, app store ratings, platform reviews — product and ops issues surface early.
PhyloAI builds a portfolio-specific ontology: which KPIs matter per company, what thresholds trigger alerts, how signals combine into distress scores, and who owns each intervention.
Stage, sector, thesis, board seat
Runway, burn, NRR, hiring, reviews
Thresholds, combinations, weights
Converging signal confidence
Founder call, bridge prep, board item
Ask what happens if a portfolio company continues current trajectory — or if you intervene now. Scenarios grounded in live signal data, not static spreadsheets.
Runway exhausts in ~8 months based on current burn and hiring deceleration signals.
Extends runway 4–6 months. Reduces distress score if hiring stabilises within 60 days.
Co. B gaining reviews while competitor hiring freezes. Recommend accelerated GTM spend.
Multi-source signals monitored continuously
Ontology explains why signals matter
Scenarios model intervention outcomes
Specific actions assigned to owners
Outcomes refine future signal rules
Every morning: priority alerts, cross-portfolio opportunities and competitor launches — ranked by severity with recommended actions per company.
See briefing format →"Which companies show early distress?" "What changed at Co. X this month?" — answered from live ontology, instantly.
Try example queries →Cross-reference founder claims against GST filings, hiring data, reviews and competitor activity — surfacing gaps before board meetings.
See diligence workflow →Detect when competitor stalls, market windows open, or portfolio companies can share resources — opportunities invisible in siloed reviews.
See opportunity example ↑Immediate alerts when multiple independent signals align — hiring + filings + reviews + founder sentiment.
See alert example ↓Board-ready summaries with signal context, intervention recommendations and outcome tracking from the last review cycle.
See briefing format →Every intervention outcome feeds back into your portfolio ontology — signal rules get sharper with each board cycle.
Fund manager schedules founder call based on converging distress signals. Action logged in PhyloAI.
Did hiring stabilise? Did runway extend? Was the signal accurate? Outcome data captured automatically.
Signal weights, thresholds and combination rules updated based on what actually predicted distress vs. false positives.
Each cycle makes the system more accurate for your specific portfolio, sector mix and investment thesis.
Tell us about your portfolio. We map your ontology and show exactly which signals PhyloAI would monitor — typically scoped as an 8-week design partnership across 5–15 portfolio companies.