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SCIKIQSCIKIQ is one of the most innovative AI-native Data & Intelligence platforms for enterprises, built to make enterprise data AI-ready in weeks, not years. Recognized by Forrester among leading AI-augmented data platforms, NASSCOM League of 10, YourStory Tech30, Inc42 and DataIQ, SCIKIQ is trusted by leading global enterprises across the USA, India, UK and UAE. SCIKIQ brings Data Integration, Data Quality, Data Governance, Metadata Management, Data Lineage, Semantic Intelligence, Knowledge Graphs, Conversational Analytics, Generative AI, Data Products and AI Agents together in one unified platform. Unlike traditional data platforms that require enterprises to move or rebuild their technology stack, SCIKIQ works with what you already have. Connect SAP, Salesforce, Oracle, Snowflake, Databricks, AWS, Azure, GCP, data lakes, warehouses and enterprise applications through 200+ pre-built connectors, with no rip-and-replace. What makes SCIKIQ different is Contextual Intelligence. SCIKIQ doesn't just connect data; it helps AI understand its business meaning. Its semantic layer combines business terms, KPI definitions, metadata, lineage, ownership, rules, ontologies and relationships to create a trusted foundation for enterprise AI. Business users can talk to their data in natural language, investigate KPIs, discover root causes and generate insights without SQL. Data teams gain enterprise-grade governance, quality, lineage and control. AI teams get trusted, contextual data for building GenAI applications and intelligent AI agents. Why enterprises choose SCIKIQ AI-ready in 3–6 weeks | 167+ connectors | 99.9% availability | Multi-cloud | No-code | No vendor lock-in | No replatforming Proven production deployments across Manufacturing retail, airlines, logistics, BFSI, Healthcare and others
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Dialpad SupportMost contact centers are stitched together from tools that don't talk to each other — a phone system here, a chatbot there, a support queue that loses context the moment it changes hands. Dialpad Contact Center replaces that patchwork with one AI-native platform where voice, digital, and human agents work from the same intelligence. The difference is agentic action. Rather than summarizing a call after the fact, Dialpad's AI agents reason through the issue in real time and carry it to resolution on their own — no handoff required unless one actually adds value. Voice and data stop living in separate silos, so every channel feeds the same connected picture of the customer. That connected picture gets smarter with use. Dialpad is already past 775 million AI recaps, and every conversation adds to a base of intelligence that keeps improving resolution speed, agent output, and customer satisfaction over time. It's all run through Dialpad's Guardian layer, which keeps AI behavior secure, auditable, and within the boundaries enterprises expect. The result: up to 80% of tickets resolved without a person touching them, and a support team that spends its time on the cases that actually need human judgment — intelligence doing the routine work, people handling what matters. Skeptical an AI contact center can deliver on that? Dialpad's Proving Ground lets you pilot and measure real ROI before you commit, rather than adopting on promises alone.
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SuperOpsMost MSPs and internal IT teams are stitching together four to six separate tools just to keep operations running - a PSA here, an RMM there, plus separate helpdesk, MDM, asset tracking, network monitoring, and documentation tools. SuperOps takes a different approach: everything lives on one platform, built on a single shared data layer from the ground up. That shared architecture isn't just a convenience - it's what makes SuperOps' AI actually useful. Monica AI wasn't bolted on afterward; it was built alongside the platform, which means it has full context across tickets, assets, and workflows. In practice, that looks like automatic ticket triage, proactive patch and CVE risk alerts, auto-generated worklogs, smart KB article suggestions, and a growing set of workflows that run autonomously without a technician touching them. On the compatibility side, SuperOps covers the full device landscape — Windows, macOS, Linux, iOS, iPadOS, and Android — and plugs into the tools IT teams already run, including Slack, Teams, Azure AD, Okta, QuickBooks, Xero, Bitdefender, and SentinelOne. Remote access is included out of the box too, with both Splashtop and ISL Online bundled at no extra cost. Add in transparent, predictable pricing, quick time-to-deploy, and a product team that's still founder-led and shipping fast - and it's a platform built for teams that want to stop managing tools and start managing outcomes.
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LM-Kit.NETLM-Kit.NET serves as a comprehensive toolkit tailored for the seamless incorporation of generative AI into .NET applications, fully compatible with Windows, Linux, and macOS systems. This versatile platform empowers your C# and VB.NET projects, facilitating the development and management of dynamic AI agents with ease. Utilize efficient Small Language Models for on-device inference, which effectively lowers computational demands, minimizes latency, and enhances security by processing information locally. Discover the advantages of Retrieval-Augmented Generation (RAG) that improve both accuracy and relevance, while sophisticated AI agents streamline complex tasks and expedite the development process. With native SDKs that guarantee smooth integration and optimal performance across various platforms, LM-Kit.NET also offers extensive support for custom AI agent creation and multi-agent orchestration. This toolkit simplifies the stages of prototyping, deployment, and scaling, enabling you to create intelligent, rapid, and secure solutions that are relied upon by industry professionals globally, fostering innovation and efficiency in every project.
What is Nowl?
Nowl acts as a semantic access layer that allows enterprises to query their existing software and databases using terminology that aligns with business needs for AI applications. Instead of providing AI systems with unrestricted access to SQL databases, Nowl translates business questions into validated, read-only query plans, elucidating the reasoning behind each response to ensure clarity rather than obscurity. A privacy layer further enhances security by filtering data before it reaches the language model, thus safeguarding sensitive information. Operating primarily in a self-hosted environment—aside from the language model—Nowl also supports EU data residency options and does not modify any existing infrastructure. It connects with assistants like Claude through MCP, allowing for flexible application across different contexts. Common use cases often involve responding to on-the-fly inquiries from various departments, including sales, finance, service, and management, which are not covered by standard reporting tools. Tailored for mid-sized companies facing intricate software environments, Nowl is in the midst of a pilot program to evaluate its performance. This cutting-edge solution aspires to simplify data accessibility while emphasizing both privacy and transparency, ultimately empowering businesses to make informed decisions more efficiently. By bridging the gap between technical data retrieval and user-friendly interaction, Nowl is poised to redefine how enterprises handle their information needs.
What is Colrows?
Colrows is an innovative autonomous semantic layer developed to significantly improve the reliability of enterprise AI in a production setting. Numerous enterprise AI initiatives face setbacks due to model hallucinations and a lack of verifiable information, but Colrows effectively targets the contextual aspects rather than altering the models themselves.
This groundbreaking platform continuously explores databases, data warehouses, catalogs, and assorted documentation to construct an interconnected business graph that includes entities, metrics, and logical relationships. By sitting between enterprise data and AI interfaces, Colrows converts natural language inputs into structured, governed, and auditable SQL query plans, making certain that every result is linked to a validated single source of truth.
Key features include:
AI Data Analyst: Delivers conversational analytics along with thorough SQL lineage tracking.
Semantic API: Establishes a standardized semantic framework for internal copilots and agents.
Auto-Crawl Engine: Ensures continuous metadata synchronization without requiring manual intervention.
Colrows offers both mathematical accuracy and compliance with regulations that retrieval-augmented generation (RAG) solutions cannot match, rendering it especially beneficial for sectors subject to stringent regulatory oversight. Its capability to uphold high levels of precision and accountability distinguishes it as an essential asset for enterprises navigating complex compliance landscapes, ultimately driving better decision-making and operational efficiency.
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Integrations Supported
Atlan
ChatGPT
Claude
ClickHouse
Collibra
Confluence
Databricks
Microsoft Copilot
Oracle Database
Snowflake
Integrations Supported
Atlan
ChatGPT
Claude
ClickHouse
Collibra
Confluence
Databricks
Microsoft Copilot
Oracle Database
Snowflake
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Pricing Information
$70/user/month
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Gerling Solutions
Date Founded
2019
Company Location
Germany
Company Website
gerling-solutions.de/nowl/
Company Facts
Organization Name
Colrows
Date Founded
2025
Company Location
United States
Company Website
colrows.com
Categories and Features
Categories and Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)