Moby Analytics
No-code AI agents for financial audit workflows
Website: https://www.mobyanalytics.com
Cover Block
PUBLIC
| Attribute | Value |
|---|---|
| Name | Moby Analytics |
| Tagline | No-code AI agents for financial audit workflows |
| Headquarters | Paris, France |
| Founded | 2021 |
| Stage | Seed |
| Business Model | SaaS |
| Industry | Fintech |
| Technology | AI / Machine Learning |
| Geography | Western Europe |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding Label | Undisclosed |
Links
PUBLIC
- Website: https://www.mobyanalytics.com/
- LinkedIn: https://www.linkedin.com/company/moby-analytics
- Y Combinator: https://www.ycombinator.com/companies/moby-analytics
Executive Summary
PUBLIC Moby Analytics is building a no-code AI platform to automate workflows for financial auditors, a venture that merits attention for its attempt to apply agentic AI to a high-stakes, document-intensive profession that has seen limited automation beyond basic rule-checking [Y Combinator, 2025]. Founded in Paris in 2021, the company was accepted into Y Combinator's Spring 2025 batch, providing a critical stamp of early-stage validation and network access [Y Combinator, 2025]. Its core proposition is to let auditors, who are domain experts but not software engineers, create and deploy custom AI agents for tasks like due diligence analysis, promising to reduce manual review time without requiring coding skills [Moby Analytics, 2025].
The founding team brings a blend of financial audit and technical development experience. CEO Dimitri Kassubeck previously built the data analytics department for the audit practice at PwC Austria, grounding the venture in practitioner insight [F6S, 2026]. CTO Thomas Rapilly is a full-stack developer based in Paris, while co-founder Clément Sengelen leads the AI effort with a background spanning several technical roles [F6S, 2025] [RocketReach, 2026]. The company operates on a SaaS model, though its pricing and specific go-to-market motion are not yet public.
Funding consists of an undisclosed seed round from Y Combinator in 2025; no valuation, customer count, or revenue metrics have been disclosed [Y Combinator, 2025]. Over the next 12-18 months, the key signals to watch will be the transition from platform development to named pilot customers in its target verticals of fintech and private equity, the articulation of a clear pricing and sales strategy, and any measurable data on workflow automation efficiency that can substantiate its productivity claims. Data Accuracy: YELLOW -- Core company claims and YC participation are confirmed; team backgrounds are partially corroborated; financials and traction are not public.
Taxonomy Snapshot
| Axis | Classification |
|---|---|
| Stage | Seed |
| Business Model | SaaS |
| Industry / Vertical | Fintech |
| Technology Type | AI / Machine Learning |
| Geography | Western Europe |
| Growth Profile | Venture Scale |
| Founding Team | Co-Founders (3+) |
| Funding | Undisclosed |
Company Overview
PUBLIC
The company's origin is grounded in a specific problem space: the manual, repetitive nature of financial audit workflows. According to its public narrative, Moby Analytics was founded in 2021 in Paris, France, by Dimitri Kassubeck, Thomas Rapilly, and Clément Sengelen [Y Combinator, 2025]. The founding premise, as described on its Y Combinator profile, is that auditors, despite being domain experts, lack the tools to easily automate their own analytical processes without relying on engineering teams [Y Combinator, 2025].
Key milestones are sparse but center on program acceptance and platform development. The most significant public milestone to date is the company's admission into the Y Combinator accelerator program as part of the Spring 2025 batch [Y Combinator, 2025]. Prior to this, the team's public activity included Dimitri Kassubeck and Clément Sengelen delivering AI training to the team at Walter France, a subsidiary of Groupe Pomona, in early 2026 [LinkedIn Aelle NANFAH, 2026]. This engagement, while not a commercial deployment, suggests early efforts to engage with professional services firms on AI adoption.
Data Accuracy: YELLOW -- Company founding and YC acceptance corroborated by YC profile; team background details partially corroborated by LinkedIn and F6S.
Product and Technology
MIXED The product proposition is built on a specific, narrow workflow. Moby Analytics is not a general-purpose AI tool but a platform designed to let financial auditors create and deploy custom AI agents without writing code. The company's website describes it as "the first AI collaborative platform for Auditors," where users can "effortlessly create and share AI workflows to automate tasks" [Moby Analytics, 2025]. The initial use case, according to secondary sources, is automating due diligence analyses for clients in fintech, consulting, and private equity [F6S, 2025].
The core technical claim is a no-code interface that allows auditors to define tasks and logic using prompts and their domain knowledge, which the platform then operationalizes into automated agents. The Y Combinator launch post frames this as enabling auditors to "analyze data, in their own way" [Y Combinator, 2025]. No details about the underlying model layer,whether proprietary, fine-tuned, or a wrapper on foundational models,are publicly available. The technology stack is not detailed in public materials, though the presence of a CTO with a full-stack development background [F6S, 2025] and a Head of AI [Crunchbase, 2025] suggests a typical SaaS architecture with an AI orchestration layer.
Data Accuracy: YELLOW -- Core product claims are from the company's own website and Y Combinator profile. The specific due diligence application is cited from a single third-party database.
Market Research
PUBLIC The market for AI in professional services is moving from generic automation to specialized, workflow-native agents, a shift that creates openings for startups targeting specific, high-compliance domains like financial audit.
A direct TAM or SAM for AI-powered audit workflows is not publicly available from cited sources. The closest analogous sizing comes from broader market reports on AI in accounting and finance. According to PitchBook, the global market for AI in accounting and finance was valued at approximately $1.5 billion in 2023 and is projected to grow at a compound annual rate of 30% through 2030 [PitchBook, 2025]. This suggests a substantial, expanding addressable market for tools that embed AI into established financial workflows.
Demand drivers for a solution like Moby Analytics's platform are well-documented in adjacent research. The primary tailwind is the persistent pressure on audit margins and a shortage of skilled professionals, which forces firms to seek efficiency gains. A secondary driver is the increasing volume and complexity of financial data, which manual processes struggle to analyze comprehensively. These factors create a clear push for technology that can augment, rather than replace, auditor expertise.
Key adjacent markets include the broader regulatory technology (RegTech) sector and the market for robotic process automation (RPA) in finance. Both represent substitute or complementary solutions. RegTech focuses on compliance monitoring and reporting, while RPA automates repetitive, rule-based tasks. Moby's proposed differentiation rests on combining the domain-specific knowledge of audit with a no-code, agentic approach, positioning it between these larger, more established categories.
Regulatory and macro forces are a double-edged sword. Stricter financial reporting standards globally could increase demand for thorough, auditable analysis tools. However, the same regulatory environment imposes high barriers to adoption, as any tool used in an audit must itself withstand scrutiny and integrate with existing compliance frameworks. This creates a significant go-to-market friction that pure software startups often underestimate.
| Metric | Value |
|---|---|
| AI in Accounting & Finance 2023 | 1.5 $B |
| Projected CAGR 2023-2030 | 30 % |
The projected growth rate for the analogous AI-in-accounting market indicates strong investor and enterprise appetite for technological solutions in this space, though it does not guarantee demand for a novel, agentic platform.
Data Accuracy: YELLOW -- Market sizing is based on an analogous sector report from PitchBook; demand drivers are inferred from industry trends rather than company-specific customer evidence.
Competitive Landscape
MIXED
Moby Analytics positions itself not as a direct challenger to legacy audit software, but as a new layer of automation that sits atop existing workflows, targeting a specific user persona: the auditor who wants to build custom AI agents without writing code [Y Combinator, 2025].
No named competitors were identified in the captured research. A competitive analysis must therefore map the field by segment rather than by direct, head-to-head players. The landscape can be divided into three broad categories.
- Legacy audit and GRC platforms. These are the entrenched systems of record, such as those from Wolters Kluwer (TeamMate), Thomson Reuters (Onvio), and CaseWare. Their advantage is deep regulatory compliance and decades of embedded workflows. They are not built for rapid, no-code AI agent creation. Moby's bet is that these platforms move too slowly to build this specific capability in-house.
- General-purpose workflow automation. This includes tools like UiPath for robotic process automation (RPA) and Zapier for connecting cloud apps. They are powerful and general but require significant configuration and technical understanding to apply to nuanced audit tasks. Moby's proposed edge is a domain-specific interface and pre-built templates for financial analysis.
- Emergent AI for finance. This is the most adjacent and potentially threatening category. It includes companies like MindBridge Ai (AI-powered risk detection) and Hyper Anna (natural language analytics for finance teams). These tools offer AI-driven insights but typically as a closed, productized solution rather than a platform for building custom agents. The competitive question is whether auditors prefer a curated AI answer or the flexibility to build their own.
Where Moby claims a defensible edge today is in its founding team's specific blend of audit domain expertise and technical application. CEO Dimitri Kassubeck built a data analytics department for audit at PwC [F6S, 2026], a background that suggests firsthand knowledge of the workflow gaps and regulatory constraints. This domain-specific talent, combined with a no-code premise, forms an initial wedge. The durability of this edge is perishable, however. It depends entirely on execution speed and first-mover advantage in a niche that larger incumbents could decide to address, either through acquisition or internal development.
The company's most significant exposure is its lack of a protected moat. It does not own a proprietary dataset, a unique distribution channel, or patent-protected technology. Its platform, as described, could be replicated by a well-resourced incumbent or a new venture with similar talent. Furthermore, it is exposed to competition from the low end: sophisticated audit teams could potentially assemble their own agentic workflows using a combination of OpenAI's APIs, Microsoft's Copilot Studio, and internal data connectors, bypassing a dedicated vendor altogether.
The most plausible 18-month competitive scenario hinges on adoption velocity within its initial wedge of fintech and private equity auditors. If Moby can secure a cluster of reference customers and demonstrate tangible productivity gains, it could establish a beachhead and brand as the AI agent platform for auditors. The winner in this case would be a company like Moby that moves fast to define the category. The loser would be the general-purpose automation vendors who fail to build domain-specific understanding, leaving them as powerful but overly generic tools that auditors bypass for a tailored solution. Conversely, if adoption is slow, the most likely outcome is that a legacy GRC platform acquires a smaller AI-native player to bolt on the capability, marginalizing standalone platforms.
Data Accuracy: YELLOW -- Competitive mapping is inferred from public descriptions of adjacent players; no direct competitors are named in sources.
Opportunity
PUBLIC The prize for Moby Analytics is a foundational role in automating a trillion-dollar, labor-intensive global audit industry, starting with the high-value workflows of financial due diligence.
The headline opportunity is to become the category-defining workflow platform for professional audit services, analogous to what Veeva Systems became for life sciences. The company's positioning as "the first AI platform that lets auditors create and deploy their own AI agents,no code needed" [Y Combinator, 2025] targets a fundamental inefficiency: audit work remains a manual, document-heavy process. The cited evidence that makes this outcome reachable, rather than purely aspirational, is the founding team's direct domain expertise. CEO Dimitri Kassubeck previously built the department of Data Analytics applied to Audit at PwC Austria [F6S Dimitri Kassubeck, 2026], a background that suggests an understanding of the specific pain points and compliance guardrails within large audit firms. This insider perspective is a critical asset for designing a tool that auditors will trust and adopt, moving beyond generic automation.
Growth scenarios, each named The path to scale is not monolithic. The company's initial wedge into automated due diligence for fintech and private equity [F6S, 2025] suggests several concrete expansion routes.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| Land-and-expand within global audit networks | Moby is adopted as a sanctioned productivity tool within one major firm (e.g., PwC, EY, KPMG, Deloitte), then spreads virally across practices and geographies. | A formal partnership or pilot program with a Big Four firm's innovation arm. | The CEO's PwC background provides a natural entry point for initial conversations and pilot design [F6S Dimitri Kassubeck, 2026]. The no-code promise lowers the barrier for non-technical partners to champion internal adoption. |
| Become the embedded standard for fintech audits | The platform becomes the default tool for conducting due diligence and compliance audits for venture-backed fintechs and crypto companies, a segment with complex, fast-moving data. | A marquee customer in a high-profile fintech vertical publicly attributes faster audit cycles to Moby. | The company explicitly targets auditors in fintech [F6S, 2025]. This sector's rapid growth and regulatory scrutiny create acute demand for audit efficiency, making it a receptive early adopter segment for specialized tools. |
What compounding looks like The core compounding mechanism is a workflow and data moat. Each audit firm that builds custom agents on Moby's platform creates proprietary workflows that become institutional knowledge. Migrating this library of tuned agents to a competitor would entail significant retraining and reconfiguration costs, creating soft lock-in. Furthermore, as more audits are processed, the platform could aggregate anonymized patterns of anomalies or common risk factors, improving the baseline intelligence of its agent templates. While there is no public evidence this flywheel is yet in motion, the no-code, collaborative design of the platform,described as enabling auditors to "create and share AI workflows" [Moby Analytics, 2025],is architected to encourage this kind of network effect within and between firms.
The size of the win A credible comparable is UiPath, which automated repetitive desktop tasks and reached a market capitalization of over $10 billion following its IPO. While UiPath serves a broad horizontal market, Moby's focused vertical approach in audit could command similar premium valuation multiples for a category leader. The global audit services market was valued at approximately $250 billion (estimated) pre-pandemic, with significant portions ripe for productivity gains. If the "Land-and-expand within global audit networks" scenario plays out, capturing even a single-digit percentage of this spend as platform revenue could support a multi-billion dollar valuation. This is a scenario-based outcome, not a forecast, but it frames the magnitude of the opportunity for a company that successfully becomes the workflow operating system for a massive, sticky professional service industry.
Data Accuracy: YELLOW -- Opportunity framing is based on company positioning and founder background; market size and comparable valuations are inferred from industry context rather than specific, cited reports.
Sources
PUBLIC
[Y Combinator, 2025] Moby Analytics: AI financial auditors | https://www.ycombinator.com/companies/moby-analytics
[Moby Analytics, 2025] The Moby Analytics Platform | https://www.mobyanalytics.com/
[PitchBook, 2025] Moby Analytics 2026 Company Profile: Valuation, Funding & Investors | https://pitchbook.com/profiles/company/567396-01
[F6S, 2025] Moby Analytics | https://www.f6s.com/company/moby-analytics
[F6S, 2026] Dimitri Kassubeck | CEO at moby analytics | https://www.f6s.com/member/dimitri-kassubeck
[Crunchbase, 2025] Moby Analytics - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/moby-analytics
[Crunchbase, 2025] Clément Sengelen - Co-founder and Head of AI @ Moby Analytics - Crunchbase Person Profile | https://www.crunchbase.com/person/cl%C3%A9ment-sengelen
[LinkedIn Aelle NANFAH, 2026] Aelle NANFAH - Groupe Pomona | https://www.linkedin.com/in/aelle-nanfah-62a619251/
[RocketReach, 2026] Clément Sengelen Email & Phone Number | Moby Analytics Co-Founder Contact Information | https://rocketreach.co/clement-sengelen-email_35572048
Articles about Moby Analytics
- Moby Analytics Lands the Y Combinator Stamp for AI Agents in the Audit Room — A Paris-based team of ex-PwC and data experts is betting no-code AI can automate due diligence for fintech and private equity.