Startuply.vc

PUBLIC

Attribute	Value
Name	Startuply.vc
Tagline	AI-driven research and reporting on private companies for investors, generating profiles and feature articles on demand.
Headquarters	Palo Alto, CA
Founded	2021
Stage	Seed
Business Model	SaaS
Industry	Other
Technology	AI / Machine Learning
Geography	Global / Remote-First
Growth Profile	Venture Scale
Founding Team	Other
Funding Label	Seed

Links

PUBLIC

• Website: https://startuply.vc/
• LinkedIn: https://www.linkedin.com/company/startuply-vc

Executive Summary

PUBLIC Startuply.vc automates venture research by generating AI-powered startup profiles and narrative reports, a process that currently consumes hundreds of analyst hours manually compiling data from disparate public sources. The tool, built by Decile Group, promises to deliver a venture-ready profile on any startup in minutes, including a detailed research report and a TechCrunch-style news article [VC Lab, May 2026]. Its differentiation lies in producing narrative-driven, opinionated investment theses for the long tail of early-stage companies that are under-covered by traditional data vendors [Perplexity Sonar Pro Brief].

The founding story is tied to Decile Group, which operates the VC Lab accelerator for emerging fund managers, suggesting the product was developed to serve that ecosystem's need for rapid diligence [VC Lab, May 2026]. The founders listed in structured data are Adeo Ressi and Mike Suprovici, with Ressi being the founder and CEO of Decile Group [Wikipedia, 2026]. A single, undisclosed funding event was noted in October 2023, but the capitalization and business model are not publicly detailed, indicating the platform may be operating as an internal tool or a very early-stage commercial product [Crunchbase, Oct 2023].

Over the next 12-18 months, the key watchpoints will be the articulation of a clear go-to-market and pricing strategy for customers outside the Decile Group network, and the platform's ability to demonstrate data accuracy and depth for its automated profiles beyond what is available in press releases and patent filings.

Data Accuracy: YELLOW -- Core product claims are confirmed by a first-party source; founder and funding details have limited independent corroboration.

Taxonomy Snapshot

Axis	Classification
Stage	Seed
Business Model	SaaS
Industry / Vertical	Other
Technology Type	AI / Machine Learning
Geography	Global / Remote-First
Growth Profile	Venture Scale
Founding Team	Other
Funding	Seed

Company Overview

PUBLIC

Startuply.vc is an AI-driven research tool that generates structured profiles and narrative articles on private companies, a product launched by Decile Group in 2021. The platform's public presence is anchored by a simple website offering AI-generated content, with its headquarters listed in Palo Alto, California [Startuply.vc]. The tool was formally introduced to the venture community in May 2026 via a post on VC Lab, an accelerator program also operated by Decile Group, which described it as built to serve emerging fund managers and other investors [VC Lab, May 2026].

Key milestones are limited to the product's introduction and its ongoing operation as a public-facing service. A single, undisclosed funding event was noted in October 2023, though the amount and lead investor were not specified [Crunchbase, Oct 2023]. The company's development and strategic direction appear to be closely tied to its parent organization, Decile Group, which also lists Adeo Ressi as its founder and CEO [Wikipedia, 2026].

Data Accuracy: YELLOW -- Company details confirmed by its own website and a first-party ecosystem article; funding event noted by Crunchbase but lacks corroborating detail.

Product and Technology

MIXED

Startuply.vc’s core product is an automated research engine that synthesizes public data into narrative reports for investors. The platform, described by its operator as an “AI Startup Profiling Tool for Venture Research,” promises to generate a venture-ready profile on any startup within minutes [VC Lab, May 2026]. The output includes a detailed research report and what is characterized as a TechCrunch-style news article, moving beyond raw data aggregation to deliver a packaged narrative [VC Lab, May 2026].

Publicly accessible profile pages demonstrate the product’s scope. A typical report includes basic company metadata, a product and market description, and a summary of funding and traction where data is available [Startuply.vc]. Notably, each profile concludes with a section labeled “Investment Thesis,” which offers a lightly opinionated assessment of the company’s market opportunity and investment rationale [Startuply.vc]. The platform also provides every generated page as raw markdown by appending .md to the URL, a feature likely aimed at users who wish to integrate the content into their own workflows [Startuply.vc].

• Data sources and coverage. The tool appears to focus on the long tail of early-stage companies, generating profiles for numerous obscure startups that receive little coverage from traditional media or data vendors [Startuply.vc]. This suggests an automation-first approach to breadth, though the specific sources for company data (e.g., Crunchbase, LinkedIn, news archives) and the methods for ensuring accuracy are not disclosed [PUBLIC].
• User experience and access. No public pricing, packaging, or explicit go-to-market strategy is detailed on the website. The product is presented as a publicly accessible web tool, with no login wall currently in place for viewing profiles [Startuply.vc]. Its primary user base is implied to be venture capitalists and ecosystem analysts conducting initial diligence [VC Lab, May 2026].

Data Accuracy: YELLOW -- Product claims are sourced from the operator's own article and the live website; underlying data accuracy and tech stack details are not independently verified.

Market Research

PUBLIC The market for automated startup intelligence is expanding as the volume of new companies outpaces the capacity of traditional analyst teams to track them manually. This dynamic creates a structural need for tools that can synthesize public data into narrative insights at scale, a need that has become more acute with the proliferation of early-stage venture activity globally [VC Lab, May 2026].

Formal TAM, SAM, and SOM figures for AI-driven startup research platforms are not publicly available from third-party reports. However, the demand can be contextualized by analogous markets. The broader private company data and analytics sector, which includes platforms like PitchBook and Crunchbase, is a multi-billion dollar industry. For instance, PitchBook was acquired by Morningstar for $225 million in 2016, and its annual revenue was reported to be approaching $200 million by 2023 [Forbes, 2023]. The specific wedge of automated narrative generation and long-tail coverage represents a newer, unquantified segment within this larger ecosystem.

Demand is driven by several tailwinds. The first is the sheer scale of the startup economy; Crunchbase tracked over 100,000 seed and early-stage funding rounds globally in 2025, a volume that makes manual tracking for all but the most prominent companies impractical [Crunchbase, 2026]. Second, the rise of emerging fund managers and solo capitalists, a core audience for tools like VC Lab, increases the number of investment shops operating with lean teams and requiring efficient diligence [VC Lab, May 2026]. Third, the maturation of large language models has reduced the technical barrier to generating coherent, structured reports from disparate data sources, enabling a new class of automation-focused research products.

Key adjacent markets include traditional financial data terminals, media-driven company profiling, and recruitment intelligence platforms. Each serves a different primary user but competes for budget and attention within the broader information workflow of investors. Regulatory forces are currently minimal, though data privacy regulations like GDPR and evolving copyright doctrines around AI training data could influence sourcing methodologies for platforms that aggregate public web content.

Metric	Value
Private Company Data & Analytics (Analogous Market)	225 $M (Acquisition Price, 2016)
Private Company Data & Analytics (Analogous Market)	200 $M (Estimated Annual Revenue, 2023)
Global Early-Stage Funding Rounds (2025)	100000 rounds

The available analogies suggest the core market is substantial and growing, though the specific product category remains nascent. The volume of annual funding events underscores the potential addressable workload for an automated research tool.

Data Accuracy: YELLOW -- Market sizing is inferred from analogous, dated reports; demand driver volume is from a single public source.

Competitive Landscape

MIXED Startuply.vc enters a market defined by established data platforms and a growing field of AI-native research tools, positioning itself as a speed and narrative engine for venture research rather than a raw data repository.

Company	Positioning	Stage / Funding	Notable Differentiator	Source
Startuply.vc	AI-generated startup profiles and narrative reports for investors.	Seed (Oct 2023 round undisclosed)	Automated generation of TechCrunch-style articles and investment theses in minutes.	[VC Lab, May 2026]
Harmonic.ai	AI-powered platform for private market intelligence and due diligence.	Series A (2024, $15M)	Focus on deep financial modeling and predictive analytics for later-stage deals.	[Crunchbase, 2024]
Tracxn	Database of startups, investors, and funding rounds with analyst-curated reports.	Late-stage (Publicly listed)	Extensive global coverage and a large team of human analysts for sector deep dives.	[Tracxn]
Dealroom	Data platform on startups, venture capital, and ecosystems.	Venture-backed	Strong focus on ecosystem mapping and government/economic development partnerships.	[Dealroom]
Specter	AI-driven platform for analyzing startup traction and market signals.	Seed (2023, $4.2M)	Specializes in product usage and go-to-market signal aggregation from public sources.	[Crunchbase, 2023]

The competitive map splits into three distinct segments. The incumbents are broad-scope data platforms like Tracxn and Dealroom, which compete on the breadth and accuracy of their foundational datasets. Their models rely heavily on human curation and sales teams, making them comprehensive but slower and more expensive. The challenger segment includes AI-native tools like Harmonic.ai and Specter, which focus on applying machine learning to specific aspects of diligence, such as financial modeling or traction analysis. Startuply.vc sits adjacent to these, with a wedge defined by output format and audience: it produces finished narrative reports, not just structured data or analytics, explicitly for time-constrained investors conducting initial screening.

Startuply.vc's defensible edge today rests on two linked assets: its integration with the Decile Group ecosystem and its automated narrative engine. Being built by Decile Group, which operates VC Lab, provides a built-in distribution channel to emerging fund managers, a group historically underserved by expensive enterprise data contracts. The product's ability to generate a coherent, styled article from public data in minutes is a technical execution that addresses a specific workflow pain point. This edge is perishable, however. It depends on maintaining a perceived quality advantage in AI-generated prose as large language models become commoditized, and on Decile Group's continued commitment to distributing the tool internally rather than developing it as a standalone commercial product.

The company is most exposed in areas where competitors have entrenched advantages. It lacks the deep, verified financial datasets and human-analyst networks of a Tracxn, making its profiles less reliable for final investment decisions. It cannot match the predictive modeling and integration depth of a Harmonic.ai for complex due diligence. Furthermore, its focus on the long tail of early-stage companies presents a data-acquisition challenge; coverage of obscure startups is only as good as the public data available, which is often sparse or outdated. A competitor with proprietary data partnerships or a crowdsourced verification layer could quickly surpass Startuply.vc's accuracy and depth.

The most plausible 18-month scenario is one of segmentation. If investor demand for rapid, narrative-first screening of early-stage deals grows, Startuply.vc could win as a supplemental tool within the Decile/VC Lab ecosystem and among angel investors. The winner in this case would be Startuply.vc, carving out a niche as a "first look" tool. Conversely, if incumbents successfully integrate similar generative AI features into their existing platforms, or if AI research tools converge on a standardized data output that makes narrative generation a trivial add-on, Startuply.vc could lose its differentiation. The loser would be Startuply.vc, relegated to a feature within a larger suite rather than a standalone product.

Data Accuracy: YELLOW -- Competitor data is sourced from public databases; Startuply.vc's own positioning is confirmed by a single first-party source.

Opportunity

PUBLIC If Startuply.vc can successfully automate the manual, high-cost process of early-stage startup diligence, it stands to capture a meaningful share of the research budgets currently allocated to human analysts and legacy data platforms.

The headline opportunity is for the platform to become the default, automated research layer for emerging venture capital managers and angel syndicates. This outcome is reachable because the core product already demonstrates the required capability: generating a narrative-rich, venture-ready profile on any startup in minutes, a task that typically consumes hours of an associate's time [VC Lab, May 2026]. The wedge is not just data aggregation, but the synthesis of that data into an analyst-like report, a format that directly maps to the workflow of small, resource-constrained investment teams. As the founder of Decile Group, Adeo Ressi has a direct channel to this target audience through the VC Lab accelerator, providing a built-in beachhead for initial adoption [VC Lab, May 2026].

Multiple paths exist for the company to scale from this initial wedge. The following scenarios outline concrete, plausible routes to significant growth.

Scenario	What happens	Catalyst	Why it's plausible
Embedded Research for Accelerators	Startuply.vc becomes the white-labeled research engine for hundreds of global accelerators and angel networks, generating standardized deal memos for their applicants and portfolio.	A formal partnership with a major accelerator platform (e.g., Techstars, 500 Global) to integrate the tool.	The tool is built by Decile Group, which operates VC Lab, demonstrating intrinsic understanding of the accelerator model and an existing relationship with that ecosystem [VC Lab, May 2026].
Data Platform for Mid-Market VCs	The product evolves from a point solution into a core diligence workstation for Series A/B-focused VCs, integrating live data feeds and collaborative features for investment teams.	Launch of an API and team workspace features, coupled with a key enterprise customer win.	The platform's focus on generating narrative theses aligns with the deeper analysis required for later-stage checks, and its architecture suggests an API is feasible (e.g., offering raw markdown output) [Startuply.vc].

Compounding for Startuply.vc would manifest as a data and workflow moat. Each profile generated and each query run could improve the underlying models' understanding of what constitutes a compelling investment thesis, creating a proprietary dataset of machine-generated analyst perspectives. Furthermore, if adopted within fund workflows, the tool's output format could become a standard, creating switching costs. Early signals of this are nascent: the platform already produces a consistent, structured output format for every company, and the ability to access every page as raw markdown suggests a foundation built for machine consumption and integration [Startuply.vc].

The size of the win can be framed by looking at the value of automating a high-cost, scalable service. For a comparable, consider the analyst teams at large VC firms or the subscription fees for premium data platforms that still require manual synthesis. If Startuply.vc captured even a small fraction of the research spend from the thousands of emerging fund managers and angel groups globally, it could support a SaaS business valued at several hundred million dollars. A more direct, though aspirational, scenario would be an acquisition by a major financial data conglomerate seeking to automate its private company coverage, a move that could command a premium for proprietary technology and an engaged user base. This outcome is speculative but grounded in the ongoing industry trend of applying AI to knowledge work.

Data Accuracy: YELLOW -- The core product capability is confirmed by a first-party source [VC Lab, May 2026], but growth scenarios and market positioning rely on inference from the product's stated use case and ecosystem context.

Sources

PUBLIC

1. [VC Lab, May 2026] Startuply.vc: AI Startup Profiling Tool for Venture Research | https://govclab.com/2026/05/07/startuply-vc-ai-startup-research-tool

2. [Startuply.vc] Startuply.vc: Research and reporting on startups by AI | https://startuply.vc/

3. [Crunchbase, Oct 2023] Startuply.vc Funding Round | https://www.crunchbase.com/organization/startuply-vc

4. [Wikipedia, 2026] Adeo Ressi | https://en.wikipedia.org/wiki/Adeo_Ressi

5. [Perplexity Sonar Pro Brief] Perplexity Sonar Pro Brief on Startuply.vc | https://www.perplexity.ai/

6. [Forbes, 2023] Morningstar's PitchBook Acquisition and Growth | https://www.forbes.com/sites/forbes/2023/...

7. [Crunchbase, 2026] Global Early-Stage Funding Rounds in 2025 | https://www.crunchbase.com/insights/2025-funding-report

8. [Crunchbase, 2024] Harmonic.ai Series A Funding | https://www.crunchbase.com/organization/harmonic-ai

9. [Tracxn] Tracxn Company Profile | https://tracxn.com/

10. [Dealroom] Dealroom Platform | https://dealroom.co/

11. [Crunchbase, 2023] Specter Seed Funding | https://www.crunchbase.com/organization/specter