Lovelace AI
Lovelace AI builds enterprise context engines that synthesize multimodal data into knowledge graphs for high-stakes decision-making in defense, intelligence, and financial services.
Raised $16M across disclosed rounds.[1][7][9]
Seed closed May 2025, led by RRE Ventures.[1][8][9][10]
post-money valuation is not publicly disclosed.
Named investors include RRE Ventures.[1][8][9][10]
Andrew Moore, Founder and CEO[1][8][9][10]
Toby Smith, Co-founder and Head of Engineering[1][7][9][14]
Matthew Houy, Head of Technical Program Management[1][7][9][14]
Adam Fisher, Head of Product (departed Apr 2026)[1][7][9][14]
Dina Mattaliano, Executive Business Partner[1][7][9][14]
Lovelace emerges from stealth with context engine that claims 1000x AI investigative power · Jun 2026[6]
Lovelace · Jun 2026[9]
Org Enrichment Data · Jun 2026[11]
Palantir Technologies · palantir.com · Same buyer (defense/intelligence), same workflow (multimodal data fusion for high-stakes decisions), and same budget. Moore directly compares Lovelace to early Palantir, claiming Palantir infrastructure cannot handle hundreds of thousands of new facts...[5]
Neo4j · neo4j.com · Same technology category (knowledge graphs) and same enterprise buyer for graph-based AI context. CIO article positions Lovelace directly against Neo4j.[5]
Perplexity AI · perplexity.ai · Same claim category (cited, verifiable AI output for complex questions), but different scale claim. Moore distinguishes Lovelace by operating at billions of facts vs. hundreds of documents.[6]
The customer proof is company-sourced only. No independent source in this ledger confirms it.[8][10]
Ask for one referenceable production customer.
Not a recommendation. The first thing this ledger cannot answer.
Filled in the side panel for invited readers. This card carries sourced facts only.
Jun 2026 · theaiinsider.tech
reported
Jun 2026 · thenewstack.io
reported
Jun 2026 · prnewswire.com
company
Jun 2026
vendor
Lovelace AI
Lovelace AI builds enterprise context engines that synthesize multimodal data into knowledge graphs for high-stakes decision-making in defense, intelligence, and financial services.
Ask for one referenceable production customer.
Not a recommendation. The first thing this ledger cannot answer.