Pinegap: Initiation of Coverage

GAII Intelligence defines the AI Research & Intelligence market as software that applies generative and agentic AI to the research process of professional investors: locating candidate securities, assembling and interrogating evidence, producing written analysis with traceable sources, and monitoring positions once held. Buyers are hedge funds, long-only managers, multi-manager platforms, family offices and allocators; the economic buyer is typically the chief technology officer, the head of research, or a portfolio manager with a technology budget.

Capabilities we treat as mandatory

• Evidence retrieval at scale: the ability to search and reason across regulatory filings, transcripts and news, and across documents the client supplies.
• Source traceability: every material claim in an output must be reachable back to the passage that supports it.
• Institutional data handling: a stated position on where client data goes, how long it is held, and whether it is used for model training.

Capabilities we treat as differentiating

• Persistent state: the system remembers a thesis, a coverage list or a position between sessions and acts on it without being re-prompted.
• Workflow surfaces: delivery inside the applications analysts already use — the spreadsheet, the research management system, email and messaging.
• Owned or exclusive content: material that a competitor cannot obtain by signing the same third-party contract.
• Published evaluation: a measured, disclosed accuracy methodology rather than an assertion of quality.

Pinegap competes with Pinegap for proactive thesis monitoring, with Hudson Labs on proxy and forensic review, and more broadly with Hebbia, Rogo and AlphaSense. Its push model and fund-letter and social coverage are its distinguishing features.

The following are the capabilities and characteristics that, in our assessment, most distinguish Pinegap within the AI Research & Intelligence market. Each is drawn from publicly documented product capability, published interviews with management, or independent hands-on review.

• Analyst design: Modules mirror a long/short analyst's routine — primer, earnings, conferences, proxy, risk and thesis tracking.
• Push agents: Scheduled and event-triggered output delivered to the analyst's inbox.
• Distribution: A verified Claude connector (June 2026) and MCP access from ChatGPT, Microsoft Copilot, Gemini and Cursor.
• Coverage beyond filings: Podcasts, X, Reddit, Substack and fund letters alongside filings and transcripts for 25,000+ companies.
• Traction claims: 100+ institutional clients and five of the top ten New York multi-managers (company).
• Disclosed model providers: OpenAI and Azure OpenAI with a Google fallback, named in policy.

The following are factors that prospective clients should weigh, and areas where our public review did not find sufficient evidence to reach a settled view. Several are common across vendors at this stage of the market and are not specific to Pinegap. We encourage prospective clients to raise each of them directly with the company; we have done the same, and will update this note as answers arrive.

• Security evidence: "SOC 2 compliance" is claimed without type, auditor or date; ISO 27001, SCIM, customer audit logs and residency options were not located.
• Compliance controls: MNPI and information-barrier controls were not located.
• Downstream training: Pinegap's no-training pledge does not address the model providers it uses.
• Content scope: No expert, broker or consensus data, and data providers are not named.
• Evaluation: No evaluation or citation controls were located.
• Inconsistent figures: Client counts ("100+ institutions" and "250+ funds"), headcount and report volumes differ across sources.
• Pricing and scale: No public pricing, and a team of about 20.

Pinegap Inc. is based at 14 Penn Plaza, New York, with engineering in Bengaluru. It was founded in 2024 by Deepak Sharma (CEO), an IIT-BHU engineer, and Ankit Varmani (CBO), who reports 15 years on the sell side and buy side including J.P. Morgan equity research. Commercial launch followed in the first quarter of 2025.

Pinegap raised a $2.5m seed in April 2024 led by SVQuad and Inventus Capital with DeVC, and an $8m Series A in August 2026 led by Stellaris Venture Partners — $10.5m in total. The company says the Series A valuation was more than triple the seed and that ARR doubled after launch; neither figure is disclosed.

Company-reported figures are shown as such and are not independently verified. Verification is carried into the vendor questionnaire.

Pinegap offers analyst workflow modules and push agents. Figure 2 sets out our assessment of how it maps onto the investment workflow.

Company modules

Overview, primer, valuation, proxy review, risk tracker and peer comparisons.

Earnings and conferences

Previews, recaps, guidance, sentiment, readthroughs and follow-up questions.

Thesis and push agents

Thesis tracker, watchlists and agents delivering scheduled or event-driven output.

MCP connector

About 32 tools via OAuth, verified in Claude and available in ChatGPT and Copilot.

Scope of the product today

We did not locate an Excel or Office add-in, expert or broker content, or public pricing.

Pinegap uses OpenAI and Azure OpenAI as primary models, Google as fallback and Perplexity for web search, according to its MCP privacy policy. A proprietary model described in 2024 has no current trace.

No evaluation results or citation controls were located.

Content covers 25,000+ companies: SEC filings, transcripts, press releases, conferences, podcasts, X, Reddit, Substack, fund letters, short interest and quotes, with market data from an unnamed provider.

Expert, broker and consensus data were not located. Clients can connect their own data.

Pinegap fits the monitoring and ramp-up stages of a fundamental analyst's work: preparing primers and earnings reviews and tracking theses.

Modelling and deliverable production are limited.

Pinegap claims SOC 2 compliance and enterprise SSO, uses OAuth 2.1 for its connector, runs on AWS US regions and publishes retention periods and its own no-training pledge. Figure 3 sets out what our public review located.

We would encourage buyers to request the SOC 2 report, SCIM and audit logs, model-provider retention terms and MNPI controls.

The offsetting factor is disclosure of model providers and retention periods, which several larger peers do not publish.

Pricing is not published; subscriptions are seat-based, with a two-week trial on request.

Buyers should compare cost against Pinegap and larger platforms.

Pinegap sits in the Emerging quadrant of the GAII Intelligence Matrix, below the Emerging band on overall score, held back by missing evidence.

GAII initiation universe, 20 October 2026. Scores as currently published on the GAII Intelligence page; preliminary and based on public information.

11.1 Where Pinegap is strongest relative to peers

• Against chat-based copilots, on push agents.
• Against larger platforms, on analyst-specific modules.
• Against peers, on social and fund-letter coverage.

11.2 Areas of narrower functional focus

Pinegap has built depth in analyst workflow rather than content or documentation.

• Enterprise: attestation unverified.
• Content: no premium content.
• Evidence: no evaluation or pricing.
• Scale: about 20 staff.

Scores are on a 0–10 scale. Each dimension score is the mean of its sub-criteria, and the GAII Overall Score is the weighted mean of the six dimensions. The detailed sub-criteria scores that build each dimension are set out in Appendix A.

These are the areas where our public review did not find sufficient evidence to form a settled view. We have put them to the company and will update this note when they are answered. Prospective clients may find them a useful agenda for their own evaluation call.

• The SOC 2 report type and period.
• SCIM and customer audit logs.
• Retention and training terms with model providers.
• MNPI and information-barrier controls.
• Named data providers.
• Citation controls.
• Evaluation results.
• Pricing.
• Reconciliation of client counts.
• Named references.
• Excel or Office export plans.
• Current headcount.

This note is an assessment of a vendor against a defined framework, not a recommendation to buy or to decline. The following are the considerations we would put at the centre of an evaluation of Pinegap specifically.

If you are a fundamental equity manager

• Trial the push agents on your watchlist.
• Compare with Pinegap.
• Check transcript and filing sources.

If you are responsible for technology or vendor risk

• Open with Figure 3; request the SOC 2 report.
• Confirm model-provider terms.
• Assess support capacity.

If you are assessing the category rather than the company

• Push agents are replacing prompt-based research.
• MCP distribution lets small vendors reach large firms.
• Evidence, not features, separates early vendors.

Each dimension score in Section 12 is the mean of the sub-criteria below.