Qualitate

Cover Block

From the public record

Field	Value
Name	Qualitate
Tagline	AI-native primary-intelligence platform for investment firms, asset managers, and corporate strategy teams [Qualitate, April 2026]
Headquarters	New York, United States [Qualitate, April 2026]
Founded	2023 [Qualitate, April 2026]
Stage	Series A [Qualitate, October 2026]
Business Model	SaaS
Industry	Fintech
Technology	AI / Machine Learning [Qualitate, April 2026]
Geography	North America
Growth Profile	Venture Scale
Founding Team	Solo Founder, Sagar Kadakia [Qualitate, April 2026]
Funding Label	$10M+
Total Disclosed	~$32,000,000 [Qualitate, April 2026] [Qualitate, October 2026]

Links

From the public record

• Website: https://www.qualitate.io/
• X / Twitter: https://x.com/S_Kadakia

The Short Version

PUBLIC Qualitate is building an AI-native primary-intelligence platform for investment firms, asset managers, and corporate strategy teams, and it merits attention now because it is trying to compress one of the slowest research workflows, expert calls and custom fieldwork, into a software product with venture backing and early enterprise-style customer claims [Qualitate, April 2026] [Insight Partners, October 2026]. Founded in 2023 in New York by Sagar Kadakia, the company positions itself as a faster alternative to traditional expert networks, with an AI Moderator that automates study design, expert recruitment, interviews, synthesis, and natural-language querying; public materials and publisher coverage repeatedly cite output across more than 10,000 public and private companies, although most operating claims still trace back to the company or financing-related coverage [Qualitate, April 2026] [Morningstar/Business Wire, April 2026] [Pulse2].

The commercial wedge is straightforward: Qualitate says custom projects typically deliver 20 to 25 in-depth interviews in three to seven business days at roughly one-third the cost of traditional expert networks, a proposition that, if it holds in production, could matter for diligence sprints, channel checks, and ongoing market monitoring where speed and repeatability are decisive [AlleyWatch, April 2026] [ExpertNetworks.net]. Product scope appears broader than a single research workflow, with public materials describing a Research Agent, Transcript Library, Company and Market Signals, Continuous Monitoring, simulations, and integrations via API and data feeds [Qualitate] [PitchBook].

The founder fit is one of the cleaner parts of the story. Kadakia is identified as Qualitate's founder and CEO, previously held a VP, Research Products and Operations role at CB Insights according to Crunchbase, and was cited by Forbes in 2020 as director of research at ETR, which supports the view that the company is being built by an operator with direct exposure to research products for institutional users [Qualitate, April 2026] [Crunchbase] [Forbes, March 2020].

On financing, the public record shows a $7 million seed round in April 2026 led by IA Ventures and Crew Capital, followed by a $25 million Series A in October 2026 led by Insight Partners, with earlier commentary from Crew Capital's Dylan Reider describing a $1.2 million pre-seed check; taken together, disclosed financing totals about $33.2 million (estimated) by summing the reported $1.2 million, $7 million, and $25 million rounds [Qualitate, April 2026] [Insight Partners, October 2026] [Dylan Reider / Infinite Runway, April 2026]. The revenue model is presented as SaaS, and the customer set described in public materials spans private equity, hedge funds, credit investors, venture funds, asset managers, and large enterprises, with the October 2026 announcement naming Alger, Stone Point Capital, Squarepoint, UiPath, Collibra, Alteryx, and Commvault as customer organizations [Citybiz, April 2026] [Qualitate, October 2026].

Over the next 12 to 18 months, the central questions are less about category interest than about proof: whether AI-moderated research can sustain compliance quality, whether the claimed cost and speed advantage translates into durable budgets, and whether a broad product surface turns into repeat usage rather than point-project demand [PitchBook] [AlleyWatch, April 2026] [Qualitate]. Hiring for roles including Chief of Staff, Senior Product Manager, Security Engineer, Account Executive, and Data Engineer suggests the company is staffing for product depth, go-to-market expansion, and enterprise readiness at the same time [Qualitate/Ashby] [Simplify Jobs, July 2026] [Dreamwork].

Single-source, plausible -- Section mixes independently corroborated funding and founder-background facts with material product and traction claims that remain primarily company-sourced or derived from financing coverage.

Taxonomy Snapshot

Axis	Value
Stage	Series A
Business Model	SaaS
Industry / Vertical	Fintech
Technology Type	AI / Machine Learning
Geography	North America
Growth Profile	Venture Scale
Founding Team	Solo Founder
Funding	$10M+ total disclosed, about $33.2M (estimated)

The Company in Brief

PUBLIC

Qualitate presents as a New York-based software company built around a simple claim: primary research for investors and strategy teams can be turned from a bespoke services workflow into a repeatable data product [Qualitate, April 2026]. Public materials date the company to 2023 and identify Sagar Kadakia as founder and CEO [Qualitate, April 2026] [Crunchbase]. The company describes itself as an AI-native primary-intelligence platform serving investment firms, asset managers, and corporate strategy teams, with headquarters in New York, United States [Qualitate, April 2026].

The public chronology is short but unusually compressed. Crunchbase places the company's founding in 2023 [Crunchbase], while the first detailed company launch materials surfaced in April 2026 alongside a $7 million seed round led by IA Ventures and Crew Capital [Qualitate, April 2026]. In October 2026, Qualitate announced a $25 million Series A led by Insight Partners and framed that financing as support for expanding its primary-research platform and customer base [Qualitate, October 2026].

Single-source, plausible -- Core company identity and timeline are supported by company materials, with founding corroborated by Crunchbase, but legal entity details are not established in the cited public sources.

What They Have Built

MIXED

The product pitch is straightforward: Qualitate is trying to compress primary research from a bespoke service workflow into software, with AI handling much of the interviewing and synthesis layer [Qualitate, April 2026]. Public materials describe an "AI-native primary-intelligence platform" built for investment firms, asset managers, and corporate strategy teams, with an AI Moderator that automates study design, expert recruitment, interviews, synthesis, and natural-language querying [Qualitate, April 2026] [Morningstar/Business Wire, April 2026]. Third-party descriptions are directionally consistent on the core mechanic, namely that the system conducts expert discussions at scale and converts conversations into structured, time-series outputs covering more than 10,000 public and private companies [Tech Company News] [Daily Research News Online] [Pulse2].

The website presents the platform as a set of connected research surfaces rather than a single workflow tool [Qualitate]. Those surfaces include a Research Agent for question-answering backed by interview evidence, a Transcript Library for searching prior expert conversations, Company & Market Signals for tracking quantified demand and buyer behavior, Continuous Monitoring for alerts, AI-Moderated Interviews for custom research, support for human-led calls and imported transcripts, Simulations for scenario testing, Embedded Intelligence for grounding agents in a user's calls and documents, Workspace & Projects for collaboration, and API, MCP, and data-feed integrations [Qualitate]. PitchBook's profile adds one notable implementation detail, reporting that the platform uses verified experts and compliance screening for material non-public information, which matters in this category because the product is only as credible as the guardrails around expert sourcing and interview handling [PitchBook].

Public claims on operating performance are promising but should be read as company-described until more independent validation appears. Qualitate says the AI Moderator can run thousands of expert discussions per month, and multiple publisher-hosted summaries repeat that framing, while AlleyWatch reports that custom projects typically involve 20 to 25 in-depth interviews delivered in 3 to 7 business days at roughly one-third the cost of traditional expert networks [Qualitate, April 2026] [Pulse2] [AlleyWatch, April 2026]. On the technical stack, the public record is thin; the only defensible inference is that the company is building for enterprise deployment and data infrastructure depth, given open roles spanning security, product, account executive hiring, and data engineering [Qualitate/Ashby] [Simplify Jobs, July 2026] [Dreamwork]. Any deeper stack reading would be speculative, so the product case here rests less on disclosed architecture than on whether the structured interview corpus and workflow automation produce decision-useful outputs at repeatable quality.

Single-source, plausible -- Core product description is corroborated across the company site, press release coverage, and PitchBook, but several feature and scale claims remain company-described or publisher-repeated rather than independently verified.

Market Size and Demand

PUBLIC The market matters now because primary research has become both more valuable and more operationally strained: investors and strategy teams want faster proprietary insight, while the traditional expert-call model remains expensive and human-labor intensive [AlleyWatch, April 2026] [ExpertNetworks.net].

Qualitate does not disclose a third-party TAM, and the available sources do not surface a named market-research report that sizes AI-native primary intelligence directly. The safer framing is to treat this as an intersection of several adjacent budgets: expert networks, custom research, and enterprise intelligence software. That is consistent with how the company is described publicly, as a product for investment firms, asset managers, and corporate strategy teams that automates study design, expert recruitment, interviews, synthesis, and natural-language querying [Qualitate, April 2026] [PitchBook].

The demand signal in the public record is less about abstract market size than about workflow pain. Qualitate and third-party coverage repeatedly position the wedge as speed and unit cost, with custom projects said to involve 20 to 25 interviews in three to seven business days at roughly one-third the cost of traditional expert networks [AlleyWatch, April 2026]. That claim sits against an external pricing benchmark in which traditional expert calls typically cost $700 to $1,500 per hour on the client side, with major networks often around $1,000 to $1,350 per hour [ExpertNetworks.net]. If those benchmarks are directionally representative, the opening is clear: compress turnaround time and convert unstructured calls into reusable datasets rather than one-off transcripts.

The buyer base also appears broader than a single research niche. Public materials place the product across private equity, hedge funds, credit investors, venture capital, asset managers, and large enterprises, and later company materials name customer organizations spanning financial services and enterprise software [Citybiz, April 2026] [Qualitate, October 2026]. That matters because adjacent demand can come from several budget owners at once: diligence teams buying channel checks, public-market investors buying faster variant perception, and corporate strategy teams buying competitive or win/loss intelligence [Qualitate, April 2026].

Cited market proxy	What it suggests	Source
Traditional expert calls priced at $700 to $1,500 per hour	Existing spend in the substitute workflow is high enough for software-led cost compression to matter	[ExpertNetworks.net]
Custom projects with 20 to 25 interviews in 3 to 7 business days	Buyers appear willing to purchase compressed-turnaround primary research, not only live calls	[AlleyWatch, April 2026]
Custom projects at roughly one-third the cost of traditional expert calls	The economic pitch is budget substitution, not only productivity tooling	[AlleyWatch, April 2026]
Customers include six of the top 15 private-equity firms	Early adoption is reported within one of the highest-value primary-research buyer groups	[Dylan Reider / Infinite Runway, April 2026]

The table does not establish a formal TAM, but it does show where the market logic rests: Qualitate is selling into a pre-existing spend pool with visible friction on cost, turnaround, and reusability. For investors, that is usually a stronger early indicator than a broad category figure assembled from unrelated software segments.

The most important tailwind is the shift from transcripts to structured intelligence. Several public sources describe the platform as turning interviews into quantified, time-series outputs that cover more than 10,000 public and private companies and can be queried in natural language [Tech Company News] [Daily Research News Online] [Pulse2]. Even allowing for company-influenced repetition in those descriptions, the direction is notable. Research buyers increasingly want systems that preserve institutional memory, support repeat queries, and feed internal workflows, rather than static reports that expire after a deal team or strategy group reads them once [Qualitate, retrieved 2026].

There are also macro and compliance angles, though the public evidence here is narrower. PitchBook describes the product as using verified experts and compliance screening for material non-public information, which aligns with a longstanding requirement in expert-network workflows rather than a new regulatory tailwind [PitchBook]. The larger macro force is budget scrutiny. Reuters reported in 2020 that corporate technology spending was expected to contract during the pandemic period, a reminder that research and software budgets can tighten quickly when end markets weaken [Reuters, March 2020]. In that setting, a vendor promising faster answers at lower unit cost may fare better than labor-heavy substitutes, but that remains an inference rather than an observed outcome for this company.

Adjacent and substitute markets deserve attention because they shape both upside and pricing pressure. The closest substitute is the traditional expert network, where clients pay for access to one expert call at a time [ExpertNetworks.net]. Adjacent markets include enterprise competitive intelligence, win/loss analysis, market-monitoring software, and research workflow tools, all of which appear in the company's stated use cases and product surface [Qualitate, April 2026] [Qualitate, retrieved 2026]. That adjacency expands the possible budget envelope, but it also means buyers may compare Qualitate not only with expert networks, but with broader intelligence platforms and internal research operations.

Single-source, plausible -- This section relies on one independent pricing benchmark, one independent profile of project economics, and several company or company-amplified descriptions of market positioning and use cases [ExpertNetworks.net] [AlleyWatch, April 2026] [Citybiz, April 2026] [PitchBook].

Who Else Is Fighting for This

MIXED

Qualitate is positioning itself less as a traditional expert network and more as a software layer that turns primary research into a searchable, structured data asset for investors and strategy teams [Qualitate, April 2026] [Qualitate, retrieved 2026].

Company	Positioning	Stage / Funding	Notable Differentiator	Source
Qualitate	AI-native primary-intelligence platform for investment firms, asset managers, and corporate strategy teams	Founded 2023; disclosed funding of about $32 million across pre-seed, seed, and Series A	Company says its AI Moderator automates study design, expert recruitment, interviews, synthesis, and natural-language querying, with outputs structured into time-series intelligence across more than 10,000 companies	[Qualitate, April 2026] [Qualitate, October 2026] [Dylan Reider / Infinite Runway, April 2026]
GLG	Incumbent expert network serving investors and enterprises	Not established in the provided public source set	Traditional human-led expert call network model	[STRUCTURED FACTS]
AlphaSights	Incumbent expert network and research services provider	Not established in the provided public source set	Scale in expert sourcing and service-led execution	[STRUCTURED FACTS]
Guidepoint	Incumbent expert network for institutional investors and corporates	Not established in the provided public source set	Established client relationships in investment research workflows	[STRUCTURED FACTS]
Tegus/AlphaSense	Adjacent substitute combining expert transcripts with searchable research workflow	Not established in the provided public source set	Workflow advantage likely rests in a searchable transcript and intelligence layer rather than only one-off calls	[STRUCTURED FACTS]
Third Bridge	Incumbent expert research platform and network	Not established in the provided public source set	Longstanding presence in institutional research and diligence workflows	[STRUCTURED FACTS]

The map breaks into three groups. Qualitate is trying to bridge those categories by automating the call-generation process and then converting interviews into quantified, time-series outputs that can be queried in natural language, which is a different claim from simply running a faster expert network [Qualitate, April 2026] [PitchBook] [Pulse2].

The strongest edge visible in public material is product architecture tied to founder-market fit, though both parts need to be treated carefully. Sagar Kadakia previously held research and data-product roles at ETR and CB Insights, and Insight Partners describes him as having more than 15 years of experience building data products for enterprises and investment firms [Forbes, March 2020] [Crunchbase] [Insight Partners, October 2026]. If Qualitate's system is in fact producing structured, longitudinal datasets from interviews at scale, the defensible layer would be the accumulated corpus and workflow integration rather than the base model layer itself; that edge could compound if customers continue to run due-diligence sprints, channel checks, and monitoring programs inside one platform [Qualitate, April 2026] [Qualitate, retrieved 2026]. It is also a perishable edge, because most of the product and throughput claims are still company-described or lightly corroborated by republished coverage rather than independently benchmarked operating data [Morningstar/Business Wire, April 2026] [AlleyWatch, April 2026].

The exposure is more concrete. Qualitate says its AI moderator performs compliance screening for material non-public information, which speaks directly to a core procurement concern, but that still leaves a burden of proof around enterprise trust, especially for large asset managers and public-company strategy teams [PitchBook] [Citybiz, April 2026]. In other words, the category opening is real, but the company is attacking a workflow where incumbents already own budget lines and analyst habits.

Over the next 18 months, the most plausible scenario is not wholesale replacement of expert networks but share capture in fast-turn, repeatable research programs. Qualitate is the winner if buyers decide that speed, lower per-project cost, and structured outputs matter more than bespoke human moderation, particularly for channel checks, win/loss studies, and continuous market monitoring; the company has publicly framed custom work as 20 to 25 interviews in days at roughly one-third the cost of traditional expert calls, and traditional calls are commonly priced around $700 to $1,500 per hour according to industry benchmarking [AlleyWatch, April 2026] [ExpertNetworks.net]. The loser if that shift accelerates would be a service-heavy incumbent such as Guidepoint or Third Bridge in the narrower slice of standardized projects.

Opportunity

PUBLIC

The prize here is unusually large if Qualitate can turn primary research from a bespoke services workflow into software that investment and strategy teams use continuously, not episodically [Qualitate, April 2026] [Insight Partners, October 2026].

The clearest upside case is that Qualitate becomes the default system of record for primary intelligence inside buy-side and corporate strategy workflows. That is a bigger outcome than being a faster expert network. The public evidence points to a product ambition that reaches beyond call scheduling and transcript capture: the company describes an AI Moderator that handles study design, expert recruitment, interviews, synthesis, and natural-language querying, alongside modules for continuous monitoring, transcript search, signals, simulations, embedded intelligence, and integrations via API and data feeds [Qualitate, April 2026] [Qualitate]. That breadth matters because the largest software outcomes in research tend to come from workflow capture plus proprietary data accumulation, not from a single point solution. The reach is still early and many claims remain company-supplied, but a $25 million Series A led by Insight Partners within months of a $7 million seed suggests investors saw enough early adoption and product surface area to underwrite a platform outcome rather than a narrow tool [Qualitate, April 2026] [Qualitate, October 2026] [Insight Partners, October 2026].

The growth paths are not identical, but they cluster around the same idea: once primary research is faster and cheaper, teams can do more of it, in more functions, and keep the output live instead of filing it away after one project. That thesis is at least directionally supported by Qualitate's claim that custom projects can deliver 20 to 25 in-depth interviews in three to seven business days at roughly one-third the cost of traditional expert networks, while traditional expert calls are commonly priced around $700 to $1,500 per hour on the client side [AlleyWatch, April 2026] [ExpertNetworks.net]. If those economics hold in production, the category boundary shifts from expert calls as a scarce input to primary intelligence as an always-on dataset.

Scenario	What happens	Catalyst	Why it's plausible
Buy-side system of record	Qualitate becomes the standard layer for diligence sprints, channel checks, and portfolio monitoring across private equity, hedge funds, and asset managers	A few visible institutions standardize on AI-moderated workflows and expand usage across teams [Qualitate, October 2026]	The company says customers already include six of the top 15 private-equity firms and asset managers with trillions in AUM, while customer segments named publicly include private equity, hedge funds, credit, venture, and asset management [Dylan Reider / Infinite Runway, April 2026] [Citybiz, April 2026]
Enterprise intelligence platform	The product expands from investors into large corporate strategy, product, and win/loss teams that need recurring outside-in intelligence	The broader product suite, including Research Agent, Company & Market Signals, Continuous Monitoring, and Workspace, gains adoption beyond deal teams [Qualitate]	Public customer references include UiPath, Collibra, Alteryx, and Commvault, and the company explicitly markets win/loss, competitive intelligence, market monitoring, and strategy research use cases [Qualitate, October 2026] [Qualitate, April 2026]
Data infrastructure layer	Qualitate's structured interview output becomes an input into internal models, dashboards, and agent workflows via API and data feeds	Product teams treat primary intelligence as machine-readable data instead of static reports [Qualitate]	The company says its platform converts interviews into quantified, time-series outputs on more than 10,000 companies and supports integrations through API, MCP, and data feeds, which is the architecture needed for embedding into downstream workflows [Tech Company News] [Qualitate]

What compounds, if the model works, is not only software revenue but data density. Each additional interview can improve transcript coverage, sector benchmarks, company-level time series, and the usefulness of natural-language retrieval across the corpus, according to the company's own product description [Qualitate]. Public materials repeatedly frame the output as structured, quantified, and time-series rather than a library of unstructured calls, and several third-party writeups echo coverage of more than 10,000 public and private companies [Tech Company News] [Daily Research News Online] [Pulse2]. That creates the outline of a flywheel: lower-cost interviews increase volume, higher volume improves the dataset, a better dataset makes the research agent and monitoring products more useful, and broader utility supports expansion from one-off projects into recurring platform spend. Early signs of that breadth are visible in the use cases Qualitate names, from due diligence and channel checks to win/loss programs and competitive intelligence, and in the customer mix spanning both investment firms and enterprises [Qualitate, April 2026] [Qualitate, October 2026].

The upside can be framed against the incumbents it is trying to compress. Traditional expert networks sell access by the hour, with client-side pricing often benchmarked around $1,000 to $1,350 per hour for major networks, according to industry pricing references [ExpertNetworks.net]. Qualitate's stated wedge is materially faster turnaround and roughly one-third the cost for custom projects, which, if sustained, gives it room either to underprice legacy workflows or to hold price while delivering much more volume [AlleyWatch, April 2026]. A plausible high-end outcome is that the company grows into a scaled intelligence platform valued more like research software and data infrastructure than like a services broker. With $32 million of disclosed funding across pre-seed, seed, and Series A, the company has at least enough capital to attempt that transition rather than proving the concept on a shoestring [Dylan Reider / Infinite Runway, April 2026] [Qualitate, April 2026] [Qualitate, October 2026].

A concrete way to size the win is to look at what happens if Qualitate captures a meaningful share of primary-research budgets now spent on traditional expert calls and adjacent custom research, then layers software-style retention on top. Expert networks routinely monetize high-value, recurring institutional workflows, and Qualitate is explicitly positioning itself as an AI-native alternative to that process [Pulse2] [PitchBook]. If the "buy-side system of record" scenario plays out, this could support a multi-billion-dollar enterprise value (scenario, not a forecast), because the product would combine recurring software spend, proprietary data creation, and deep workflow integration across some of the highest-value research users in finance and enterprise strategy [Insight Partners, October 2026] [Qualitate, October 2026]. The public record does not provide enough independent financial data to anchor a tighter range, but the shape of the upside is clear: replacing paid hours with a compounding intelligence dataset is the kind of category shift that can produce outsized outcomes when it works.

Single-source, plausible -- Built primarily from company materials, investor writeups, and limited third-party coverage; funding is corroborated across multiple public sources, while product performance and customer-scale claims are only partially corroborated.

Sources

From the public record

1. [Qualitate, April 2026] Announcing Qualitate | https://www.qualitate.io/news/announcing-qualitate

2. [Insight Partners, October 2026] Behind the Investment: Qualitate | https://www.insightpartners.com/ideas/behind-the-investment-qualitate/

3. [Morningstar/Business Wire, April 2026] Qualitate Raises $7 Million to Bring Expert Intelligence into Every Investment and Strategy Decision | https://www.morningstar.com/news/business-wire/20260421109536/qualitate-raises-7-million-to-bring-expert-intelligence-into-every-investment-and-strategy-decision

4. [AlleyWatch, April 2026] Qualitate Raises $7M to Deliver Expert Intelligence in Days Instead of Weeks at One-Third the Cost | https://www.alleywatch.com/2026/04/qualitate-ai-moderator-primary-research-ai-expert-intelligence-network-alternative-platform-sagar-kadakia/

5. [Crunchbase] Sagar Kadakia - Founder & CEO @ Qualitate - Crunchbase Person Profile | https://www.crunchbase.com/person/sagar-kadakia

6. [Dylan Reider / Infinite Runway, April 2026] From First Check to Full-Time | https://www.infinite-runway.com/p/from-first-check-to-full-time

7. [Citybiz, April 2026] Qualitate Raises $7 Million Seed Round to Build AI Research Platform for Investors and Corporates | https://www.citybiz.co/article/834839/qualitate-raises-7-million-seed-round-to-build-ai-research-platform-for-investors-and-corporates/

8. [Qualitate, October 2026] Our $25M Series A and the next decade of primary research | https://www.qualitate.io/news/qualitate-announces-25m-series-a

9. [Qualitate] Continuous Intelligence · Qualitate | https://www.qualitate.io/

10. [PitchBook] Qualitate 2026 Company Profile: Valuation, Funding & Investors | https://pitchbook.com/profiles/company/1081560-07

11. [Qualitate/Ashby] Chief of Staff job listing | https://jobs.ashbyhq.com/qualitate/639e6e43-a398-437e-b19c-c91b20b2d4d1

12. [Simplify Jobs, July 2026] Senior Product Manager job listing | https://simplify.jobs/p/01c9771a-90a3-4e0b-8005-5e66922f62ac/Senior-Product-Manager

13. [Forbes, March 2020] Five Things To Expect From Cuts In CIOs’ Tech Budgets Due To COVID-19 | https://www.forbes.com/sites/martingiles/2020/03/20/five-things-to-expect-cio-it-budgets-coronavirus/?sh=636541e649b1

14. [Reuters, March 2020] Coronavirus may cut global corporate tech spending 4.1% in 2020: survey | https://www.reuters.com/article/us-heatlh-coronavirus-technology/coronavirus-may-cut-global-corporate-tech-spending-4-1-in-2020-survey-idUSKBN21I38C

15. [X, August 2026] Sagar Kadakia (@S_Kadakia) on X | https://x.com/S_Kadakia