From “Rifle Shot” Patents to Portfolio Machines

How patent acquisition + licensing-first strategies are reshaping litigation finance (2025–2026)

Why the patent playbook is changing

The classic retail mental model for “patent investing” is a single big case: one patent, one defendant, one huge payout. That can happen, but it comes with brutal downsides: binary outcomes, long timelines, validity challenges, and incentives that sometimes don’t align with settlement reality.

Two things are happening at the same time:

The opportunity set is big: high-tech markets (devices, networks, semiconductors) produce lots of infringement surface area and large damages pools.
The old structure is fragile: a single-case bet can be derailed by one adverse claim construction, one invalidity finding, one jurisdictional issue, or just time.

Meanwhile, the patent litigation backdrop remains active:

Higher activity: Lex Machina reported a 22% surge in filings and $4.3B in damages in its 2025 report covering 2024 results.
NPE share remains large: Unified Patents reported NPEs filed 55.4% of U.S. district court patent cases in 2025.
SEPs are a major arena: A LexisNexis report noted U.S. SEP litigation roughly doubled from 2014 to 2024, with PAEs driving a large share.

The new playbook: build a patent platform, not a single case

A strategy trend that’s becoming more common is to shift from “one case bets” into a platform approach:

1) Acquire families of related patents

Instead of a single asset, the platform accumulates a portfolio (often a “family” of related patents) so the thesis isn’t dependent on one claim construction or one court outcome.

Why families matter (in plain English):

Multiple paths to infringement: if one claim reads narrowly, other claims/patents may still map to product implementations.
Less “one patent kills the deal” risk: a validity loss on one patent is less fatal when the campaign isn’t concentrated.
Better negotiating leverage: a target facing multiple credible patents has fewer “easy” design-around options.

A common implementation is to build (or partner with) a patent acquisition vehicle that owns the patents and runs a consistent licensing program. The key point is that the “asset” isn’t a case — it’s a repeatable licensing engine supported by litigation when needed.

2) Lead with licensing (the “carrot”), keep litigation as the credible “stick”

The platform offers targets a businesslike license path first. Litigation is the escalation mechanism for “unwilling licensees.” Conceptually, the goal is to make “voluntary license” the rational decision versus multi-year litigation uncertainty.

What “carrot and stick” looks like operationally:

Carrot: well-prepared outreach backed by evidence-of-use, clear scope, and an offer that looks cheaper than litigation risk.
Stick: credible readiness to file (or expand) litigation in a venue/jurisdiction where the patent(s) are likely to survive and where damages are meaningful.

Licensing-first is not “nice.” It’s a filtering mechanism. If targets can settle for a rational number early, the platform reduces duration and cost. If targets won’t engage, the platform escalates selectively.

How the workflow runs (step-by-step)

Step	What happens	Why it matters
1. Asset selection	Acquire patents that map to high-volume products and have survivable validity profiles.	Bad patents create “dead campaigns” no matter how good the lawyers are.
2. Evidence-of-use build	Map claims to product components, implementations, standards, or chip features.	Licensing without proof-of-use is weak; proof turns “maybe” into “pay attention.”
3. Target list + prioritization	Rank targets by exposure, ability to pay, and settlement predictability.	Pick battles where time-to-cash is realistic.
4. Licensing outreach	Offer a license with clear terms and a credible deadline.	Turns litigation into the expensive alternative.
5. Selective enforcement	File a “test case” (or a small set) against the most strategic holdouts.	Creates pressure and improves licensing conversion on the rest.
6. Portfolio expansion	Add more patents / claims to maintain leverage as products evolve.	Prevents targets from waiting out a narrow case thesis.

3) Reduce binary risk with portfolio finance

At the funder/law-firm level, litigation finance has been moving toward portfolio and cross-collateralized structures, where wins and losses are pooled so one loss is less likely to wipe out the economics. Burford has written publicly about how law firms use portfolio finance.

In portfolio finance, the “collateral” is not a single case. It’s a pool of cases (or fee interests) where recoveries are aggregated. This can reduce binary risk, but it also introduces a new question:

What exactly is being cross-collateralized, and who gets paid first?

Most portfolio structures still have a waterfall: capital back first, then a preferred return (if any), then profit splits. The details determine whether a “great headline win” actually translates into investor distributions.

What enables this strategy: diligence is getting more industrial

This approach only works if the funder can quickly and repeatedly answer: “Who is using this technology, and can we prove it?” Increasingly, groups use teardown / reverse-engineering datasets and evidence-of-use workstreams to support infringement mapping and target selection.

One example of publicly marketed tooling is TechInsights’ teardown and “evidence of use” offerings, which are designed to connect real-world products/components to technical features relevant for IP analysis.

Why this matters specifically in semiconductors/high-tech: infringement often depends on what’s inside devices (chips, dies, packaging, firmware behavior). Proving that at scale is expensive. If a platform can spread that diligence cost across many targets and many related patents, it gets leverage that “one-off” investors rarely have.

What “industrial diligence” tries to reduce

False positives: thinking a patent maps to a product when it doesn’t (wasted campaign).
False negatives: missing the best targets because the diligence didn’t go deep enough.
Adverse selection: ending up with patents that look good on paper but fail in real-world claim charts.

Reality check: gross vs net still matters

Even if the underwriting thesis is strong, investor outcomes depend heavily on structure, fees, loss rates, and time-to-cash. Legal Funding Journal has a good discussion of how commercial litigation finance can show meaningful gross vs net return dispersion.

At a high level, gross case outcomes must cover losses, time, and fees (often across multiple layers) before you see attractive net results.

This is why serious due diligence always asks for net-to-LP expectations, not just “our best case returned 3x.” The sections below break down where the gap usually comes from.

Investor lens: what you’re actually buying

When someone says “patent litigation finance,” they could mean very different products:

Structure	What it is	What investors should watch
Single-case funding	Capital goes into one lawsuit (or one claim cluster) with a defined return schedule.	Extreme binary risk; one loss can wipe the investment. Check return caps and control/settlement terms.
Portfolio funding	Capital is secured by a pool of cases (often at a law firm). Recoveries are cross-collateralized.	Less binary, but waterfalls can delay LP distributions. Understand what is cross-collateralized and repayment priority.
Patent acquisition platform	A vehicle owns patent families and runs licensing + selective enforcement as a repeatable engine.	Great if diligence is real; disastrous if “evidence-of-use” is weak or validity risk is ignored.
Blind-pool fund	A manager raises a fund and allocates across many opportunities over years.	Manager skill dominates. You’re underwriting the underwriter. Track record + incentives matter more than any single case study.
Feeder / wrapper	An extra entity invests into the main vehicle (often with its own fees, reserves, tax structure).	Fee stacking and tax effects. Make sure you understand “net to you,” not “net to the underlying fund.”

Investor lens: the fee stack (why “gross” can mislead)

Litigation finance often has multiple layers of cost between “case outcomes” and “what you receive.” A simplified (generic) fee stack looks like:

Manager fee: typically charged annually (sometimes on committed capital during the investment period).
Operating + diligence costs: underwriting teams, expert networks, monitoring, admin, audits, legal.
Carry/promote: profit split after a preferred return and catch-up (varies by fund).
Wrapper fees: if you’re in a feeder, there can be an additional fee layer.
(Optional) leverage/insurance costs: if the structure uses debt and/or principal protection, those costs sit senior in the waterfall.

None of this is “bad” by itself. The investor question is whether the manager’s underwriting edge is strong enough to clear the fee stack after losses and time.

Toy model: how gross turns into net

Below is an intentionally simplified example to show mechanics. These are not forecasts for any specific fund.

Item	Example	Notes
Capital committed	$100	What you agree to invest.
Capital actually deployed	$85	Some funds don’t deploy 100% (timing, early resolutions, or conservative pacing).
Gross portfolio result (before fund costs)	1.80x on deployed	$85 → $153 gross proceeds.
Losses inside the portfolio	(included above)	Some investments can be total losses; the gross number already “nets” wins and losses at the portfolio level.
Manager fee + expenses	$8	Over multi-year holds, fee drag compounds even if MOIC looks fine.
Carry/promote	$7	Depends on waterfall (pref + catch-up + split).
Net distributions to LP	$138	$153 – $8 – $7 = $138 → 1.38x net MOIC.

Even in this friendly example, gross 1.80x on deployed becomes ~1.38x net to LP. Now add duration: if that takes 6–7 years, the IRR can look very different than if it resolves in 3–4 years.

Waterfalls: where “who gets paid first” matters

For many private funds, distributions follow a waterfall that often resembles:

Return of capital to LPs (and sometimes repayment of any facility/line if used).
Preferred return to LPs (if the fund uses a pref).
Catch-up to the manager (varies).
Profit split (e.g., 80/20) between LPs and manager.

If a structure includes leverage or principal protection, debt service and senior claims can sit above equity distributions. That can make early-years cashflows look “quiet” even if cases are resolving—because senior layers get paid first.

Taxes and wrappers: small print that changes outcomes

Patent monetization can generate different tax character depending on structure (and jurisdiction). If there’s a wrapper entity (for example, a corporate blocker or a feeder vehicle), you can end up with:

Different reporting: K-1 vs 1099 (depends on structure).
Tax drag at the entity level: in some corporate structures, gains are taxed before distributions.
Different character: ordinary vs capital (often varies by deal type).

This is not a reason to avoid a deal; it’s a reason to demand clarity on “net to you after tax assumptions,” and to model your own situation.

Investor checklist (questions that cut through sales copy)

Track record / reporting

Do they report net-to-LP MOIC and DPI (not just IRR)?
Are unrealized positions marked conservatively (cost) or fair-valued—and is the method consistent?
Can they reconcile prior forecasts vs current forecasts (what changed and why)?

Portfolio construction

How concentrated can any single investment get (by commitment and by deployed)?
What % is single-case vs portfolio structures?
How is “portfolio” defined: cross-collateralized firm-level agreements or just “a bunch of cases”?

Patent acquisition platform specifics

What is the evidence-of-use standard before outreach?
How do they handle validity risk (IPR strategy, prior art diligence, kill rate)?
What is the licensing conversion strategy (and what are the typical blockers)?

Economics

Fees: management fee base (committed vs deployed) and how it steps down in harvest.
Carry: hurdle/pref, catch-up terms, and whether carry is deal-level or fund-level.
Expected call pace and expected distribution timing (and what “normal delays” look like).

Red flags

Lots of “gross case wins” but little clarity on net and cash returned.
Overconfident timing claims in an asset class defined by legal duration uncertainty.
FOMO sales process: “decide fast” without enough data to underwrite.

Bottom line

The industry trend is moving away from “one patent / one case” bets toward repeatable patent platform strategies: acquire families, build proof-of-use at scale, lead with licensing, and use litigation selectively to convert holdouts. This can reduce binary risk and improve bargaining power — but the strategy is only as good as (1) the diligence and (2) the net economics after fees, duration, and losses.