Companies

Eden

tryeden.ai

AI sales simulation software creates realistic buyer roleplays, scores representatives, and prepares revenue teams for live calls.

HQNew York City, New York, United States
Employees1-50
Specialization
Speech
Business
Software Applications
Market
Cross Industry
Ecosystem
Not classified
Customers
Enterprises
More details
Organization type
Commercial Company
Ecosystem
Not classified
Business
Software Applications
Specialization
Speech
Market
Cross Industry
Customers
Enterprises
Delivery models
Hosted Software
Revenue models
Not classified
Listing status
Not classified
Latest equity round
Pre Seed
Reported funding amount
Not classified

About

The company behind tryeden.ai now presents itself as Quotain, an AI sales simulation platform for revenue teams. It turns CRM notes, past calls, LinkedIn profiles, and company websites into realistic AI buyers, then scores practice calls and produces objections, coaching feedback, and playbooks—differentiating through deal-specific preparation rather than generic sales training.

Market

Eden competes in AI infrastructure and governance, combining an AI gateway/control plane with governed access to models, tools, APIs, data, and database-migration capabilities. Its differentiation is the broader scope beyond model routing: Eden authenticates callers, resolves scoped credentials, applies proxy-layer controls, supports data access and migrations, and emphasizes an open-source gateway and no-code database migration rather than only AI request routing.

Target Customers

Eden is aimed at growth-stage and enterprise engineering, platform, data-infrastructure, and security teams—especially in industries such as retail and insurance—that operate AI-powered applications, handle sensitive data, and need governed access to models, tools, APIs, and databases. Likely buyers are CTOs, VP Engineering, platform leaders, data-infrastructure leaders, and security teams responsible for AI governance and database modernization.

At a Glance

Problem

Eden, whose current tryeden.ai site presents the product as Quotain, addresses a persistent sales-execution problem: representatives often enter important calls without enough practice, while conventional sales training becomes a box-checking exercise rather than preparation for the specific opportunity in front of them. The economic pain is material: Quotain cites average quota attainment of roughly 50% and argues that reps need to ramp in weeks rather than months, because missed deals, slow onboarding, and manager coaching time directly depress revenue.

The killer use case is deal-specific preparation before a live pipeline call. A rep can simulate the actual prospect, rehearse discovery, a demo, negotiation, or objection handling, identify likely questions and objections, and leave with a stronger talk track and playbook for the real conversation.

Product / Service

Quotain is an AI sales-simulation and roleplay platform for revenue teams. It turns a company’s product, ideal-customer profile, sales process, and deal context—along with inputs such as CRM notes, past calls, LinkedIn profiles, and company websites—into a realistic AI buyer. Reps conduct voice-based practice sessions, then receive transcripts, scorecards, objection analysis, corrections, and a refined playbook they can use on the actual call.

The delivery model is a software platform aimed at both individual sellers and sales managers. Beyond one-off meeting preparation, it supports onboarding, repeated enablement practice, and manager coaching through team metrics and rubric-based performance signals; it is designed to connect with revenue-team systems such as Salesforce, HubSpot, Gong, Slack, and enablement repositories. The intended benefit is to make practice continuous and operationally relevant while giving managers a clearer view of where coaching will improve performance.

Market

Eden/Quotain competes in sales enablement, AI sales simulation, and conversational roleplay software. Its closest alternatives include Second Nature, which offers AI roleplays for discovery, objection handling, and demos, and Allego, whose broader AI sales-enablement platform combines training, coaching, content, and digital selling. Quotain’s differentiation is its emphasis on simulations built around each rep’s real prospects and live pipeline rather than generic training scenarios.

The company appears to be an early-stage, venture-backed startup rather than a scaled vendor. Y Combinator lists Quotain as an active Summer 2025 company founded by Alexander Talamonti and Jason He, and company records identify a $500,000 2025 pre-seed round from Y Combinator. By June 2026, Quotain said some users were practicing for more than an hour a day, but the evidence gathered does not disclose customer counts or revenue, so its precise commercial stage—and whether it is technically pre-revenue—cannot be confirmed.

Founders & Leadership

Alexander TalamontiFounder
Co-Founder & CEO
Jason HeFounder
Co-Founder & CTO

Funding History

2025-08
Pre-Seed$500K

Y Combinator

Recent News

2026-06-10product_launch
Quotain Trust Center describes AI sales execution platform

Quotain describes its platform as helping revenue teams practice roleplays, score calls, and use customer context to improve sales execution with AI. The current tryeden.ai site identifies the product as Quotain, indicating a transition from the Eden branding.

2025-09-14other
Eden AI Agents Revenue & Valuation (2025)

GetLatka reported estimated 2025 annual recurring revenue of $330,000, a $990,000 valuation, three employees, and categorized Eden AI Agents as conversational-intelligence software.

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Business Model

Quotain monetizes as a B2B subscription-style SaaS product sold to revenue teams through quote-based pricing and demo-led sales. Its website directs prospects to book a demo rather than publishing self-serve pricing.

Products

Eden governed control plane and open-source data gatewayEve for governed AI accessAdam for agent accessExodus for database and system migrationsPortEden data firewall for scoped, audited, and revocable agent data access

Tech Stack

LLMs and AI modelsAI/data gateway and proxy layerDatabases and database-migration infrastructureAPIsSecrets-management integrationSQLite-native data accessRedis vector database for planned RAG, semantic caching, and vector inference

Competitors

Bifrost by Maxim AI
Credo
Microsoft Azure API Management
Helicone AI Gateway
LiteLLM
Portkey
Kong AI Gateway