Sector-Agnostic, Not Thesis-Free: How We Pick Early-Stage Ventures

8 min read

Dariia VasylievaFounder & CEO, GETVISION

Sector-agnostic investing means we do not decide in advance which industry will produce the best companies. It does not mean we invest in anything. We replace the sector bet with five filters that every deal must pass: problem severity, AI leverage, capital efficiency, regional advantage and a credible path to exit.

The reason is practical. In emerging markets, the strongest opportunities often sit between sectors, such as a fintech product built for farmers or a logistics platform that is really a payments business. A narrow sector thesis would screen out exactly the companies we most want to see.

The filters come after the founder, not instead of the founder. At GETVISION, our founder-first thesis is the gate. The filters below decide which founders' businesses fit a portfolio that has to return capital.

Key takeaways

Sector-agnostic is a method, not the absence of one, because five explicit filters replace the single bet on an industry.
The filters are problem severity, AI leverage, capital efficiency, regional advantage and path to exit, scored on the same scale for every deal.
Venture returns follow a power law, so the job is to find outlier potential wherever it appears, not to pick the right sector early.
Real diversification means spreading currency, regulatory and exit risk, not just adding more industries to the list.
The common traps are tourist investing, thesis drift and shallow diligence, and each one has a specific fix.

Why a sector thesis breaks down in forming markets

A sector thesis works when each sector produces enough deals to choose from. In a forming market, it rarely does. RISE Research's 2026 report on Central Asia counted 370 unique funded startups across the whole region over three years. Split that by sector, and a specialist sees a handful of fundable companies a year. Meanwhile the opportunity is broad: the GETVISION ASIA opportunity map for Kyrgyzstan alone runs from AI and fintech to mountain tourism, logistics, healthcare, agribusiness and light industry.

Selection is already severe without a sector filter. In a survey of almost 900 venture capitalists by Gompers, Gornall, Kaplan and Strebulaev (Journal of Financial Economics, 2020), the average firm screened about 200 companies a year and made about four investments. Narrowing the funnel by sector before the screen even starts shrinks an already small pool.

The math of returns also argues against an early sector bet. Correlation Ventures' analysis of more than 21,000 venture financings from 2004 to 2013 found that almost two-thirds failed to return the capital invested, and only about 4% returned 10x or more. When a few outliers drive the whole portfolio, the question is not which sector will win. It is whether this company could become one of the outliers.

A sector thesis tells you where to look; filters tell you what you are looking at.

The five filters that replace a sector thesis

Each filter has one question, a passing answer and a failing answer.

Problem severity

The question: Is the customer paying for this problem today, in money, time or risk?

What passes: A problem with a budget line, a workaround the customer already pays for, or a regulatory requirement that forces action.

What fails: A problem the founder finds interesting but the customer quietly tolerates.

AI leverage

The question: Does AI change the unit economics of this business, or only its pitch?

What passes: AI that removes a cost that used to grow with every customer, such as manual underwriting, document processing or field visits. We cover this filter in depth in AI-driven startups in emerging markets.

What fails: A thin interface on a third-party model that the next platform update could replace.

Capital efficiency

The question: How much revenue, or proof, does each dollar raised buy?

What passes: A business that reaches its next milestone on the round it is raising, with a plan that does not assume a large follow-on round in a market where few exist.

What fails: A model that only works with growth-stage funding the region does not yet supply.

Regional advantage

The question: Why does this company win here, and why could it not be built just as easily from somewhere else?

What passes: Local data, licenses, language, distribution relationships or a cost structure that a foreign entrant would take years to replicate.

What fails: A copy of a global product with no local edge, waiting for the global original to arrive.

Path to exit

The question: Who could buy this company, or our stake, within a normal venture holding period?

What passes: A short list of named strategic buyers, a sector where private equity is active, or a business that can generate cash for dividends or buybacks.

What fails: An exit story that depends entirely on an IPO in a market with a thin listings pipeline.

The scoring grid

We score each filter from 1 to 5 using the same anchors for every deal, regardless of sector. The founder assessment sits above the grid as a gate: a weak founder signal stops the process before scoring begins.

Filter	Score 1	Score 3	Score 5
Problem severity	Nice to have	Budgeted by some customers	Paid for today, urgent
AI leverage	Cosmetic	Improves margins	Changes the cost curve
Capital efficiency	Needs a large follow-on	Reaches the next milestone	Near break-even on this round
Regional advantage	Easily copied	Some local edge	Hard to replicate locally
Path to exit	IPO only	One plausible buyer type	Several named buyers

Three rules keep the grid useful rather than decorative:

A score of 1 on any filter stops the deal, whatever the total.
Scores are set before the valuation discussion, so price does not change the judgment of quality.
Every score needs a written reason and one piece of evidence, so a colleague can challenge it.

Diversification logic

Being sector-agnostic makes diversification easier, but it does not make it automatic. A portfolio of six companies in six sectors can still be one bet if they share the same hidden risk.

We diversify along five axes, not one:

Sector: no single industry dominates the capital deployed.
Currency: a mix of companies earning in local currency and companies earning in hard currency.
Country and regulator: exposure spread across jurisdictions, so one policy change does not hit everything at once.
Stage: early checks balanced with follow-on capacity kept for the companies that earn it.
Exit route: different likely buyers, so a closed IPO window or a quiet M&A year does not freeze every exit together.

Currency and exit risk are the two that sector diversification most often hides. We break both down in pricing risk in frontier markets.

Common traps of sector-agnostic investors

Sector-agnostic investors fail in predictable ways. Each trap has a fix.

Tourist investing

What it looks like: An investor backs a company in an industry they do not understand, on the strength of the founder's pitch alone.

Why it hurts: Without domain context, the investor cannot tell a hard problem from an unsolved one, or help the company after closing.

The fix: For every deal outside known territory, bring in a domain expert before the decision, not after.

Thesis drift

What it looks like: Sector-agnostic quietly becomes whatever is fashionable this year, and half the pipeline follows the same trend.

Why it hurts: The portfolio concentrates in one theme at peak prices, which is the opposite of diversification.

The fix: Review the portfolio against the five axes every quarter and cap exposure to any single theme.

Shallow diligence

What it looks like: Every deal gets the same generic checklist, because nobody has the depth to go further in each sector.

Why it hurts: Sector-specific risks, such as licensing in fintech or land rights in agribusiness, surface after the money is in.

The fix: Keep a sector-specific diligence module for each industry in the portfolio, and add to it after every deal.

Frequently Asked Questions

It means an investor does not limit the portfolio to predefined industries. Instead, every opportunity is judged against the same set of criteria, such as problem severity, capital efficiency and path to exit.

It carries different risks rather than more. Sector-agnostic investors risk shallow diligence and weak post-investment help, while sector-focused investors risk concentration in one industry cycle and missing companies that sit between sectors.

Most use a structured set of criteria, typically team, problem, market, business model and terms, and rate each on a fixed scale. A good grid uses the same anchors for every deal and treats some weaknesses as disqualifying regardless of the total score.

Yes. A thesis can be built on criteria instead of industries, such as founder quality, use of AI, capital efficiency or regional advantage. Without explicit criteria, sector-agnostic turns into opportunistic, and results become hard to repeat.

Across sectors, currencies, countries, stages and likely exit routes. Diversifying only by industry can leave a portfolio exposed to a single currency, regulator or buyer pool.