Prompt2Prod.AI

Prompt2Prod.AI: Elevating AI-Generated & Vibe Coded Projects to Production Readiness Prompt2Prod.AI specializes in transforming AI-generated code, vibe-coded projects, and AI MVPs into robust, scalable, and secure production-ready solutions. This service is designed for businesses and developers who have rapidly prototyped using AI tools but now require professional engineering to meet real-world demands without costly rewrites. Key Features: AI Code Hardening: Audits and remediates AI-generated code for security vulnerabilities, scalability issues, and performance bottlenecks. Vibe Coded Project Rescue: Untangles, fixes, and documents fast-built, fragile projects, making them maintainable. AI MVP to Production Solution: Transforms prototypes into architecturally sound products with proper testing, observability, and resilience. OWASP-Aligned Security Hardening: Conducts comprehensive security audits to address common AI-generated code flaws like exposed secrets and missing input validation. Performance Optimization: Profiles systems to identify and resolve bottlenecks, leading to faster, leaner, and more cost-effective operations. Architecture Review & Scalability: Implements sound architectural patterns and scalability strategies tailored to product growth. Use Cases: Prompt2Prod.AI is ideal when your AI-generated code is functional but fragile, insecure, or unable to scale beyond a few users. If your vibe-coded project is breaking, difficult to maintain, or riddled with hidden bugs, this service provides the necessary rescue, adding tests and addressing security gaps. Furthermore, if your AI MVP has proven its concept but needs to withstand real user load, scrutiny, and become a reliable product, Prompt2Prod.AI engineers it for production, ensuring it holds up under demanding conditions. Pricing Information: Pricing is scope-based, with engagements typically commencing with a fixed-price Production Readiness Assessment. Subsequent hardening and recovery work is then quoted against an agreed-upon plan, ensuring transparency before any work begins. User Experience and Support: The process is streamlined for speed and clarity: an initial message, a focused assessment call, followed by a detailed Production Readiness Report. Hardening and delivery are systematic, with regular updates and thorough documentation for seamless handover. Clients work directly with senior engineers, ensuring direct, jargon-free communication and rapid ramp-up times. Inquiries receive responses within hours, and readiness reports are delivered in days. Technical Details: Prompt2Prod.AI works across the full stack, including Backend & APIs (Node.js, Python, TypeScript, REST, GraphQL, Microservices, Serverless), Frontend (React, Next.js, Vue, TypeScript, Tailwind CSS), Data & Storage (PostgreSQL, MongoDB, Redis, SQL optimization), Cloud & Infrastructure (AWS, GCP, Docker, Kubernetes, Terraform, CI/CD), and AI & LLM integration (OpenAI APIs, RAG pipelines, Agentic systems). They leverage AI tools like Cursor, Copilot, and Claude in their own workflow, providing deep insight into AI-generated code's common pitfalls. Pros and Cons: Pros: Specialized expertise in AI-generated code; direct access to senior engineers; rapid assessment and project ramp-up; focus on targeted fixes over full rewrites; comprehensive security and performance enhancements; thorough documentation. Cons: No explicit free trial or freemium option; service-based model rather than self-service platform; pricing is custom-quoted after initial assessment. Conclusion: Prompt2Prod.AI offers invaluable services for transforming innovative AI-driven prototypes into robust, secure, and scalable production systems. By combining senior engineering judgment with AI-assisted analysis, they ensure your projects are genuinely reliable and ready for real-world deployment. Request a Production Readiness Assessment to take your AI project to the next level.

spinyield

spinyield introduces an innovative ad market designed to monetize the "thinking moments" of AI coding agents. It allows developers to passively earn income by displaying a single, non-intrusive sponsored line in their AI agent's status bar while it processes tasks. This platform ensures 70% of every ad dollar goes directly to the developer, flat and without tiers, making it a highly developer-centric monetization solution. Targeting the 20M+ developers utilizing AI coding agents like Claude Code, spinyield offers a unique opportunity to transform idle waiting time into a revenue stream, while providing advertisers with a precise channel to reach engineers at a critical moment of focus. Key Features High Developer Share: Developers receive a flat 70% of every ad dollar, ensuring maximum earnings. Proof-of-Inference: Every impression is backed by a real AI inference, making it un-farmable and guaranteeing genuine engagement. Non-Intrusive Advertising: Ads appear as a single, tiny sponsored line in the AI agent's status bar, never in code, output, or as banners. Live Bid Market: Advertisers compete in real-time auctions for ad placements, ensuring fair pricing and optimal reach. Privacy-First Design: The system never reads your code, prompts, or files, prioritizing developer privacy and security. Easy Integration & Control: Simple one-line terminal command or one-click VS Code installation, fully opt-in, and instantly reversible. Use Cases For developers, spinyield serves as an effortless way to offset API bills or tool subscriptions. Imagine your AI agent, Claude Code, pausing to "think" during a complex refactoring task. Instead of simply waiting, a small sponsored line appears in your status bar. This passive earning mechanism accrues funds from the very first verified impression, with cash-out options starting from just $10 via Stripe. It's designed to be a supplementary income, turning unproductive waiting time into a valuable asset. For advertisers, spinyield offers an unparalleled opportunity to reach highly engaged engineers. Businesses can bid for the "thinking moment" – a prime window when developers are actively watching their agent's progress. This ensures ads are seen by a relevant audience at a moment of high attention, leading to more effective campaigns for products, services, or tools aimed at the developer community. The live bid market ensures competitive pricing and optimal ad placement. Pricing Information spinyield operates on a revenue-sharing model where 70% of every ad dollar generated from impressions, clicks, and signups goes directly to the developer. The remaining 30% is retained by spinyield to operate the network. Advertisers participate in a live bid market, paying per verified impression, with higher rates for clicks and verified signups. Developers can cash out their accrued earnings from $10 via Stripe. User Experience and Support The user experience is designed for simplicity and non-disruption. Installation is a quick, one-minute process, either via a terminal command or a VS Code click. The system is explicitly opt-in and can be switched off at any time. A "fail-silent" design ensures that if the API is unavailable, no ad appears, preventing any disruption to the developer's workflow. Developers have access to a dashboard to audit their earnings, which are tracked in a double-entry ledger. Comprehensive documentation and a full walkthrough are available on the install page. Technical Details spinyield is built to integrate seamlessly with AI coding agents. Currently, it supports Claude Code in both CLI and VS Code environments across macOS, Linux, and Windows, with Codex on the roadmap. The system relies on an API for ad delivery and a robust Proof-of-Inference anti-fraud layer. This layer binds every impression to a cryptographically signed session, verified against various signals to ensure authenticity and prevent fraud, without ever accessing the user's code or prompts. Pros Generates passive income for developers during AI agent thinking time. Highly privacy-focused; never reads user code or prompts. Non-intrusive ad placement (single line in status bar). Transparent and auditable earnings with a 70% developer share. "Proof-of-Inference" ensures genuine, un-farmable impressions for advertisers. Easy installation and complete control (opt-in/opt-out). Cons Earnings are supplementary and depend on advertiser demand. Compatibility relies on AI agent vendors not making breaking changes. Currently limited to Claude Code, with Codex on roadmap (future expansion expected). Not a primary income source, positioned as covering API bills/tools. Conclusion spinyield offers a groundbreaking solution for developers to monetize their AI agent's idle time and for advertisers to reach a highly targeted technical audience. Its commitment to privacy, transparency, and a developer-first revenue model makes it a compelling platform. Explore spinyield today to start earning passively or to connect with your next thousand customers.

LLMWise

LLMWise is a cutting-edge multi-model AI chat platform designed to provide transparent, cost-optimized access to a wide array of large language models (LLMs) from a single, unified interface. It empowers users to leverage models like GPT, Claude, Gemini, DeepSeek, and more, ensuring efficiency and cost control for individuals and teams. Target Audience: LLMWise is ideal for developers, product teams, and businesses seeking to optimize their LLM API spend, streamline model management, and avoid vendor lock-in by intelligently routing requests across various AI providers. Key Features Auto-Routing for Cost Optimization: Automatically routes prompts to the cheapest healthy model available for your plan, significantly reducing API costs. Transparent Cost Per Response: Every answer clearly displays which model was used and its exact cost, fostering trust and enabling precise budget management. Multi-Model Access: Chat with top AI models including GPT, Claude, Gemini, DeepSeek, Qwen, Llama, and more, all from one dashboard. Side-by-Side Model Comparison: Compare responses from different models for a single prompt to select the best output for your needs. Developer-First API: Offers a robust REST API with Python and TypeScript SDKs under active development, supporting streaming and easy integration. Bring Your Own Keys (BYOK): Route requests through your existing provider contracts while still benefiting from LLMWise's routing and traceability. Use Cases LLMWise excels in scenarios where cost efficiency and model flexibility are paramount. For everyday tasks, its "Auto" routing feature intelligently directs prompts to more affordable open-source or mid-tier models, preventing unnecessary expenditure on premium models. This allows users to maintain high productivity without incurring excessive costs, making it perfect for routine content generation, summarization, or coding assistance. Furthermore, LLMWise is invaluable for experimentation and quality assurance. Users can compare outputs from various advanced models like Claude, GPT, and Gemini side-by-side for critical tasks, ensuring they select the most accurate or creative response. Once the optimal model is identified, they can switch back to Auto for subsequent, less critical interactions, maintaining a balance between performance and budget. This approach simplifies the complex process of managing multiple AI APIs, consolidating them into a single, user-friendly platform. Pricing Information LLMWise operates on a freemium model, offering a "Free" tier for initial exploration (5 messages, Auto only). The "Starter" plan is available for $29/month, providing 10M tokens with Auto-only routing. For advanced users and teams requiring manual access to premium models like GPT, Claude, and Gemini Pro, the "Teams" plan is priced at $99/month for 40M tokens. Enterprise solutions with custom limits and support are also available. User Experience and Support The platform is designed with an "Auto-first" philosophy, aiming for a simple and intuitive user experience where model selection is often handled automatically. The transparent display of model and cost for every response builds trust. For developers, LLMWise provides comprehensive Python and TypeScript API guides, along with REST API documentation, to facilitate seamless integration and development. While SDKs are under active development, the existing API is robust. Technical Details LLMWise provides a native API that uses the familiar role/content message format, similar to OpenAI's, and supports streaming. It offers developer previews for Python and TypeScript SDKs, with a fully functional REST API available for immediate use. The platform is built to be developer-first, allowing for flexible integration into existing workflows. Pros and Cons Pros: Significant cost savings through intelligent Auto-routing. Transparent, per-response cost visibility. Access to a wide range of LLMs from a single interface. Simplified LLM management and reduced vendor lock-in. Supports Bring Your Own Keys (BYOK). Cons: Manual selection of premium models (GPT, Claude, Gemini Pro) is only available on the higher-tier "Teams" plan. SDKs (Python, TypeScript) are still under active development, though REST API is available. Conclusion LLMWise stands out as an intelligent and cost-effective solution for anyone looking to harness the power of multiple AI models without the complexity and expense typically associated with them. By prioritizing automatic routing and transparent pricing, it offers a streamlined path to advanced AI capabilities. Explore LLMWise today to optimize your LLM usage and unlock significant savings.

Pitch Protocol

Pitch Protocol is an innovative AI agent-native venture protocol designed to revolutionize fundraising for founders building agent-native companies. Its primary purpose is to connect these founders with thesis-aligned investors efficiently, bypassing traditional, time-consuming methods. This platform caters to founders leveraging AI in their daily operations and venture capitalists seeking high-quality, pre-screened deal flow."Key FeaturesAgent-to-agent venture protocol for seamless interaction.Accelerated 48-hour pitch-to-decision timeline.Automated, intelligent matching with investor theses across multiple dimensions (stage, sector, region, business model).Submit one structured pitch to reach every relevant VC.Investors proactively reach out to matched founders, eliminating cold outreach.Agent-driven context packaging and submission from various AI clients.Use CasesFor Founders: Pitch Protocol empowers AI agents to autonomously package and submit comprehensive company context, including team, product, traction, and market details. The protocol's agent then scores this pitch against a vast network of fund investment theses, instantly surfacing strong matches. This eliminates the need for traditional pitch decks, warm introductions, and extensive networking, significantly accelerating the fundraising process and allowing founders to focus on building. It's ideal for agent-native companies looking to raise capital in a way that aligns with their operational ethos.For Investors: Venture capitalists can define their precise investment thesis, including preferred stage, sector, check size, and specific deal breakers. Pitch Protocol's agent then delivers pre-evaluated deals with detailed thesis-fit scores, traction summaries, and pre-answered diligence questions. This drastically reduces the time spent on deal triage and improves the quality of inbound deal flow, ensuring investors only review opportunities that genuinely align with their strategy.Pricing InformationPitch Protocol operates on a 'free' model for founders and AI agents to apply. Investors can also join the network and set up their thesis profiles at no cost, receiving pre-screened deal flow without obligation.User Experience and SupportThe platform emphasizes ease of use with a simple 'install in one command' setup for both founders and investors. Founders can trigger submissions from popular MCP clients like Claude and Cursor, with their agents handling context packaging. Investors define their thesis once, and their agents automatically score incoming deals. Comprehensive guides are available, covering topics like 'Pitching an AI startup to VCs' and 'How AI agents are changing fundraising,' to assist users.Technical DetailsPitch Protocol leverages an 'MCP server' and integrates with various 'MCP clients' (e.g., Claude, Cursor), functioning as an 'API endpoint for capital.' It processes 'structured context packets' to enable agent-to-agent communication and evaluation, signifying a robust, protocol-driven architecture designed for the machine economy.Pros and ConsPros:Rapid fundraising decisions (48 hours).Highly efficient and accurate thesis-based matching.Significantly reduces manual fundraising effort for founders.Delivers high-quality, pre-screened deal flow for investors.Native integration with AI agents for seamless operations.Founders maintain control over data sharing.Cons:Requires familiarity with AI agent platforms/integrations.Potential initial learning curve for agent setup.Specific details on advanced customization are not explicitly provided.ConclusionPitch Protocol stands as a groundbreaking solution, transforming venture capital into a programmable and verifiable network built for the AI-native era. It offers unparalleled efficiency, alignment, and speed for both founders and investors. Explore Pitch Protocol today to experience the future of fundraising and deal sourcing, where your AI agent runs the round.

Odysseus AI

Odysseus AI: The Private AI Workspace for Autonomous Agents and Deep Research Odysseus AI offers a private AI workspace designed for autonomous agents, deep research, and source-traceable workflows. Built with Zero-Data-Retention (ZDR) routing, it ensures absolute data sovereignty for users. This platform is ideal for individuals and teams requiring a secure, isolated environment for high-stakes analysis and structured intelligence gathering. Key Features Zero-Data-Retention (ZDR) Routing: Guarantees absolute data sovereignty and privacy, ensuring no user data is retained or used for model training. OpenRouter BYOK Support: Connect your own OpenRouter API key for strict ZDR routing, billing control, and model choice flexibility. Autonomous Agents & MCP: Deploy agents with secure, read-only access to selected files, memory, and custom MCP server context for full execution without data leakage. Deep Research Capabilities: Transform URLs, PDFs, and notes into structured, source-traceable briefs automatically. Isolated Memory: Retain generated insights, saved sources, notes, and prior reports as reusable context for future agent runs, building a private knowledge base. Verifiable Source Ledger: Every claim in generated reports can be traced back to its underlying material, ensuring accuracy and trust. Use Cases Odysseus AI empowers users to deploy autonomous agents across private files to generate institutional-grade research without data leakage. For academic and technical literature reviews, it allows users to bring in PDFs, standards, and notes, then deploy a research agent to produce structured reviews with strict citation-style source tables. Businesses can leverage Odysseus AI for competitor and product benchmarking by adding documentation, pricing pages, and internal notes. The agent synthesizes this information into a benchmarking brief with traceable evidence. Similarly, for market intelligence and OSINT, users can save analyst reports, press releases, and market data to run autonomous loops that produce structured market briefs for review and verification. In due diligence and investment research, securely upload materials and public filings to build comprehensive diligence briefs where every claim is traceable to the source. Pricing Information Odysseus AI offers three paid plans: Starter ($190/yr), Pro ($390/yr), and Max ($990/yr), with options for annual or monthly billing. Each plan includes a specific number of research reports, estimated managed agent runs, saved sources, and workspace storage. All plans support OpenRouter BYOK for scaling beyond included managed usage and come with a 30-day money-back guarantee. User Experience and Support The platform provides an intuitive workflow: securely connect and upload various file types (PDFs, Markdown, TXT) into an isolated workspace. The engine structures these sources into a highly organized context window, allowing users to delegate research parameters to autonomous agents with strict execution limits. Users can then inspect the generated briefs, verify source tables, and audit agent actions, retaining insights for seamless follow-up tasks. The focus is on a controlled, auditable environment for serious AI workflows. Technical Details Odysseus AI operates as an isolated cloud workspace, emphasizing Zero-Data-Retention (ZDR) routing and optional OpenRouter BYOK. This architecture ensures absolute data sovereignty, as Odysseus does not train models on user files, prompts, notes, sources, or outputs. Agents are granted zero default access, interacting only with explicitly authorized URLs, files, and tools for each session, reinforcing a secure and private environment. Pros and Cons Pros: Absolute data sovereignty with Zero-Data-Retention (ZDR) routing. Enhanced privacy and control via OpenRouter BYOK. Source-traceable reports for verifiable insights. Powerful autonomous agents for complex research tasks. Isolated workspace prevents data leakage. No telemetry by default, ensuring a privacy-first experience. Cons: No free tier available for initial exploration. Requires user to manage OpenRouter API key for BYOK. Potential learning curve for optimizing agent delegation and parameters. Relies on external model providers (OpenRouter) for AI processing. Conclusion Odysseus AI stands out as a robust, private AI workspace for organizations and individuals who demand security, control, and verifiability in their AI-driven research and agent workflows. Its commitment to zero-data-retention and source traceability makes it an invaluable tool for high-stakes analysis. Explore Odysseus AI today to transform your private files into actionable, auditable intelligence.