From private markets to full-stack investing: Inveniam acquires Swarm, a bet on asset-management evolution

From private markets to full-stack investing: Inveniam acquires Swarm, a bet on asset-management evolution

On 9 December 2025 Inveniam Capital Partners announced it will acquire Swarm, a blockchain platform focused on compliant tokenisation and trading of digital securities, with the transaction expected to close in Q1 2026. Financial terms were not disclosed.

*Why this matters: complementary strengths*
The acquisition pairs Inveniam’s data-centric infrastructure for private markets with Swarm’s tokenisation and trading layer. Inveniam has been building a “digital middle office” that stitches together permissioned data, valuation workflows and AI tooling for real-world assets, a capability it has been expanding through partnerships (notably with AI group G42) and prior bolt-ons. The Swarm deal promises a single vendor able to ingest private-market data, tokenise assets compliantly and offer trading/ secondary market plumbing. That vertical integration is what Inveniam calls a “full-stack” platform for asset management.

*Strategic rationale: agentic, AI-native markets*
Inveniam’s public statements stress the next phase: making private markets “agentic” i.e., AI-native investment systems that can value, trade and manage assets with automated agents while data sovereignty and auditability are preserved. Swarm brings market-facing token issuance and trading rails, whereas Inveniam supplies the valuation, reporting and data governance layer. The combination reduces friction for asset owners who want tokenised liquidity without ceding control of sensitive data.

*Backing and scale: where Inveniam stands financially*
Inveniam has attracted institutional capital and strategic partnerships over the last 12-24 months: UAE AI group G42 announced a strategic investment in Inveniam in December 2024 and Inveniam’s cumulative fundraising has been reported at roughly $120 million. The company has used that capital to expand its product set and make targeted acquisitions (Hedgehog, Storj) and investments (a $20 million stake in MANTRA earlier in 2025). These moves show Inveniam has the funding and strategic partnerships to attempt a platform play at scale, though precise revenue or profitability figures remain private.

*The market opportunity: tokenisation is still early but fast-growing*
Estimates for the tokenised-assets opportunity vary. Tokenised market capitalisation across asset classes could plausibly reach about $1-4 trillion by 2030 under different scenarios, with a central estimate near $2 trillion as per market sources. The potential upside for a successful full-stack platform is therefore large, but timing and adoption remain the central uncertainties.

*Risks and frictions: why execution is not guaranteed*
1. Regulation: Tokenised securities must follow strict financial laws. When companies launch big tokenised products, they need approvals from regulators and must work closely with licensed custodians to stay compliant.
2. Liquidity: Tokenisation makes assets easier to split and trade, but real buying and selling activity depends on whether exchanges list these assets and whether big investors and market-makers participate. Without them, trading will remain low.

*What success would look like*
If Inveniam integrates Swarm smoothly and leverages its G42 AI partnership, success could look like: steady growth in institutional token issuances (real-estate, private credit), daily valuation feeds for thousands of assets, fee revenues from subscription valuation services plus trading/ secondary fees and partnerships with major custodians/ exchanges.

*Conclusion*
The Inveniam-Swarm tie-up signals a deliberate move to own both the data and the token rails that could one day make private markets function with the transparency and speed of public markets. The road to wide adoption will be uneven, regulatory and liquidity gaps persist, but the combination aligns with where many institutions want to go: safer, auditable tokenisation coupled with AI-driven analytics.

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