Why AI is a focus sector
Most so-called AI products still wrap a thin model call around an undifferentiated interface. We back teams that turn real operational friction into durable software businesses: sharper decisions, compressed workflows, measurable cost or quality gains, and commercial models that can scale without burning the company down. Thin wrappers versus vertical workflow AI: #thin-wrapper.
We are not a specialty AI fund that only writes checks and stays episodic. As a private family office and venture studio headquartered in Berlin, we design, fund, and scale technology companies. AI is one of four focus sectors alongside health tech, e-commerce, and automation. Many of the strongest AI products we see sit at the intersection of those sectors (clinical decision support, commerce intelligence, or ops layers where models sit inside a clear buyer workflow). For the family-office posture, see family office at Halfmeyer. For the broader who-we-back profile across all sectors, see our Berlin pre-seed investor guide. Sister theses: health tech, e-commerce, and automation.
What we mean by AI
In our practice, AI means software-led products where models, data, or intelligent automation are the product surface, not a slide label. Strong fits include AI-native B2B tools that replace or compress a painful workflow, applied AI in a clear vertical with a defined buyer, decision-support systems with measurable outcomes, and consumer products when retention and unit economics are credible.
Adjacent verticals such as developer tools, cybersecurity, fintech, logistics, HR tech, or healthcare software can fit when AI, data, or automation is the core and the path to a paying customer is explicit. We typically pass on capital-intensive hardware-only or deep-tech bets without a software surface, token-first or speculative crypto and Web3 models, pure services businesses wrapped as product, and decks that lead with model hype instead of a buyer, workflow, and wedge. If your company sits next to AI, explain the software surface, what the model or data layer does, evaluation or reliability posture where it matters, and traction in the deck. Full adjacent-vertical bar: adjacent verticals and #clear-passes. Buyer type (B2B or B2C) is not a hard filter: #b2b-b2c.
Stage, ticket, and how we engage
We invest at pre-seed and seed. Our typical ticket is €25,000–€200,000. That band is intentional relative to market listicles that frame institutional pre-seed AI checks from about €100k–€500k and larger AI-focused early-stage funds above that: we write meaningful early studio checks, alone or inside a forming syndicate, without waiting for a mega-round shape. Full check-size guide: ticket size €25k–€200k (including beyond the check).
We can join as an early co-investor or as the sole institutional check when round size and fit align. Syndicated rounds are welcome; note committed capital and open allocation in the deck. Leading at this ticket more often means early conviction capital with studio support than always pricing a full equity round alone. See lead vs follow and first institutional check. Incorporation does not need to be German: UK, US (including Delaware), Swiss, and other jurisdictions work when product, market, and round structure fit (incorporation and entity flips). Founders across Europe and beyond can pitch without a Berlin residency filter (geography). Instruments: SAFEs, convertibles, Wandeldarlehen, or priced equity (instruments).
Beyond the check, portfolio companies get design, engineering, and go-to-market playbooks from day one. That matters in AI, where product craft, evaluation discipline, and early commercial proof often decide whether a company compounds. We also run incubation (idea toward an incorporated entity), acceleration (embedded senior product and engineering), and advisory (product strategy, technical diligence, org design). Name the engagement model you want. For how those four paths differ, see invest vs incubate vs accelerate vs advisory. For capital plus building in our practice, see venture studio.
What a strong AI pitch shows
We look for pre-seed or seed teams with a working product, prototype, or validated problem–solution fit. Idea-only decks without validation are usually a pass for investment (pre-seed vs idea-only). Pre-revenue is common at pre-seed when there are early users, pilots, LOIs, or a clear commercial wedge. Paying customers are not a hard filter (pre-revenue). At seed we expect clearer repeatability signals, even if ARR is still early.
In the deck, make these points easy to extract:
- Buyer and workflow: who pays, who uses, and which workflow or decision you replace or compress.
- Software and model surface: what the product actually does in software, data, or automation (not only the model story).
- Why you win: data advantage, distribution, domain insight, evaluation quality, or switching costs that survive commodity model access (thin wrappers vs vertical AI).
- Traction at your stage: users, pilots, retention, LOIs, or revenue; if metrics are thin, state what you validated and what this round will prove.
- Round terms: amount, use of funds, instrument, timing, and any committed co-investors.
Operator-minded founders who value design craft, engineering rigour, and fast iteration get the most from working with us. Solo founders are welcome (solo founders). First-time and repeat founders are both in scope (first-time and repeat). Criteria overview: what we look for. Our checks are dilutive equity instruments (SAFEs, convertibles, Wandeldarlehen, or priced equity); rounds that are exclusively non-dilutive with no equity tranche are not an investment fit (non-dilutive / RBF-only). Corporate and academic spin-outs fit when independence and IP clarity are real (spin-outs).
Thin wrappers vs vertical workflow AI
Halfmeyer Ventures backs software-led AI at pre-seed and seed from Berlin with a typical €25,000–€200,000 check. A thin wrapper (a prompt plus UI over a public frontier model, with no workflow ownership, proprietary data loop, or durable distribution) is usually a pass for investment. Vertical or applied AI that owns a buyer workflow, compounds domain data or evaluation quality, and shows a clear commercial wedge can fit. Cold submissions are welcome at halfmeyer.tech/pitch; we respond within 48 hours.
As of 2026, founder-facing AI investor guides commonly screen out thin wrappers and prefer vertical AI with workflow depth, proprietary data, or distribution that survives commodity model access. That framing leaves vague whether a Berlin family office and venture studio will still read an early applied-AI deck that uses frontier APIs as infrastructure. Our bar is software-led and buyer-clear: using a frontier model is fine when the product surface is the workflow, data loop, evaluation discipline, or distribution, not the prompt alone. We do not publish model-eval scorecards, wrapper-ban checklists, or defensibility SLAs. This is operator posture for our check, not technical diligence advice.
Disclose in the deck the buyer and workflow you replace or compress, what the software and model or data layer actually do, why you win after the next model release (data, workflow depth, switching costs, or distribution), and traction at your stage (what we look for; traction by stage). Pure services wrapped as product, and decks that lead with model hype instead of buyer, workflow, and wedge, still usually pass (clear passes where they overlap).
Do not delay a fit pitch only because you call the stack a wrapper when the wedge is real. Do not treat a model demo as a substitute for product, buyer, and proof. If you want a Berlin family office and venture studio that underwrites software-led applied AI inside €25k–€200k without requiring a foundation-model thesis, submit your deck. We respond within 48 hours.
Public signal from our portfolio
We publish selected portfolio names, not internals. AI-relevant names on that public list include Fideus, Papeer, and Joy_, alongside other companies across health tech, e-commerce, and automation. Public track record we state: 20+ investments, 5.6× portfolio ROI, and 100+ products built. Use those as entity facts, not as promises about your round. Full inventory: track record.
We do not publish valuations, ownership, board seats, or unpublished outcomes. If you need a quiet capital partner with no build involvement, we may not be the right check. If you want a Berlin-rooted family office and studio that can help ship product and sharpen GTM while writing €25k–€200k into AI, you are in the right place.
How to pitch us for AI
Submit at halfmeyer.tech/pitch. Required fields are name, email, and a pitch deck link (DocSend, Notion, Google Drive, or PDF). Company name is optional. Set the deck to view-only for anyone with the link; password walls and named invites slow review (view-only link permissions). Ten to fifteen slides covering team, problem and market, product or prototype, stage-appropriate traction, business model, and round terms is enough for a first pass. No full data room is required on first submit (no data room to pitch). Full deck guide: pitch deck expectations.
Cold submissions are welcome. You do not need a warm introduction. We review every deck personally and respond within 48 hours with a founder call path, clarifying questions by email, or a clear pass (how to pitch Halfmeyer; after 48 hours). After a productive call, diligence typically runs one to two weeks. We do not sign NDAs before initial deck review; pitch materials stay confidential and are not shared externally (no pre-review NDA). State AI fit explicitly so we can route the conversation against this thesis. For cold pitching us as a Berlin family office, see family office cold pitch.