
StackAI is an enterprise AI automation platform built to help organizations create end-to-end internal tools and processes with AI agents. Unlike point solutions or one-off chatbots, StackAI provides a single platform where enterprises can design, deploy, and govern AI workflows in a secure, compliant, and fully controlled environment.
Using its visual workflow builder, teams can map entire processes — from data intake and enrichment to decision-making, reporting, and audit trails. Enterprise knowledge bases such as SharePoint, Confluence, Notion, Google Drive, and internal databases can be connected directly, with features for version control, citations, and permissioning to keep information reliable and protected.
AI agents can be deployed in multiple ways: as a chat assistant embedded in daily workflows, an advanced form for structured document-heavy tasks, or an API endpoint connected into existing tools. StackAI integrates natively with Slack, Teams, Salesforce, HubSpot, ServiceNow, Airtable, and more.
Security and compliance are embedded at every layer. The platform supports SSO (Okta, Azure AD, Google), role-based access control, audit logs, data residency, and PII masking. Enterprises can monitor usage, apply cost controls, and test workflows with guardrails and evaluations before production.
StackAI also offers flexible model routing, enabling teams to choose between OpenAI, Anthropic, Google, or local LLMs, with advanced settings to fine-tune parameters and ensure consistent, accurate outputs.
A growing template library speeds deployment with pre-built solutions for Contract Analysis, Support Desk Automation, RFP Response, Investment Memo Generation, and InfoSec Questionnaires.
By replacing fragmented processes with secure, AI-driven workflows, StackAI helps enterprises cut manual work, accelerate decision-making, and empower non-technical teams to build automation that scales across the organization.
Learn more

Clazar is the leading Enterprise Cloud GTM Platform built to help cloud Go-to-Market teams list, transact, and scale revenue across AWS, Microsoft Azure, and Google Cloud marketplaces. Designed for modern SaaS and enterprise technology companies, Clazar unifies the entire cloud marketplace lifecycle into one powerful system, helping teams close deals faster, eliminate operational bottlenecks, and unlock exponential growth through hyperscaler channels.
From compliant marketplace listings to private offer creation, contract execution, usage-based metering, and revenue reconciliation, Clazar automates every step of the cloud sales cycle with zero operational lift. Revenue teams can launch listings in days, generate private offers in minutes, and manage renewals and complex sales motions seamlessly, all from a single platform built for speed and scale.
Clazar integrates directly with Salesforce and HubSpot, enabling sellers, partnerships leaders, RevOps, and finance teams to run marketplace and co-sell motions inside the tools they already use. With bi-directional sync between the CRM and cloud partner portals, teams gain real-time visibility into the pipeline, offer stages, billing, payouts, and forecasting.
Clazar also empowers organizations to accelerate co-selling with hyperscalers by automating referrals, governance workflows, approval chains, and partner reporting. With embedded automation, advanced analytics dashboards, and enterprise-grade compliance, Clazar helps teams scale marketplace operations confidently without adding headcount.
Trusted by 300+ high-growth companies, including Zapier, Supabase, Replit, Pinecone, Perplexity, Confluent, and Secureframe, Clazar is the platform powering the next generation of cloud marketplace success.
Learn more
Lunary
Lunary acts as a comprehensive platform tailored for AI developers, enabling them to manage, enhance, and secure Large Language Model (LLM) chatbots effectively. It features a variety of tools, such as conversation tracking and feedback mechanisms, analytics to assess costs and performance, debugging utilities, and a prompt directory that promotes version control and team collaboration. The platform supports multiple LLMs and frameworks, including OpenAI and LangChain, and provides SDKs designed for both Python and JavaScript environments. Moreover, Lunary integrates protective guardrails to mitigate the risks associated with malicious prompts and safeguard sensitive data from breaches. Users have the flexibility to deploy Lunary in their Virtual Private Cloud (VPC) using Kubernetes or Docker, which aids teams in thoroughly evaluating LLM responses. The platform also facilitates understanding the languages utilized by users, experimentation with various prompts and LLM models, and offers quick search and filtering functionalities. Notifications are triggered when agents do not perform as expected, enabling prompt corrective actions. With Lunary's foundational platform being entirely open-source, users can opt for self-hosting or leverage cloud solutions, making initiation a swift process. In addition to its robust features, Lunary fosters an environment where AI teams can fine-tune their chatbot systems while upholding stringent security and performance standards. Thus, Lunary not only streamlines development but also enhances collaboration among teams, driving innovation in the AI chatbot landscape.
Learn more
Amazon Bedrock Guardrails
Amazon Bedrock Guardrails serves as a versatile safety mechanism designed to enhance compliance and security for generative AI applications created on the Amazon Bedrock platform. This innovative system enables developers to establish customized controls focused on safety, privacy, and accuracy across various foundation models, including those hosted on Amazon Bedrock, as well as fine-tuned or self-hosted variants. By leveraging Guardrails, developers can consistently implement responsible AI practices, evaluating user inputs and model outputs against predefined policies. These policies incorporate a range of protective measures like content filters to prevent harmful text and imagery, topic restrictions, word filters to eliminate inappropriate language, and sensitive information filters to redact personally identifiable details. Additionally, Guardrails feature contextual grounding checks that are essential for detecting and managing inaccuracies or hallucinations in model-generated responses, thus ensuring a more dependable interaction with AI technologies. Ultimately, the integration of these safeguards is vital for building trust and accountability in the field of AI development while also encouraging developers to remain vigilant in their ethical responsibilities.
Learn more