Compare Software.com vs. Teambit

Jellyfish, the top Engineering Management Platform, provides complete visibility into engineering organizations, their work, and their operations. Jellyfish analyzes engineering signals from Git, Jira, and contextual business data such as roadmapping, incident response, calendar, and collaboration tool. This allows engineering leaders to align engineering decisions and business initiatives, and deliver the right software on time and efficiently. Jellyfish allows engineering leaders to focus their teams on the most important things for the business, driving strategic decision-making and delivering results.

Cortex Internal Developer Portal allows engineering organizations to easily gain visibility into services and deliver high-quality software. Scorecards allow teams to focus on what is most important to them, such as service quality, production ready standards, and migrations. Cortex's Service Catalog integrates with popular engineering tools to give teams an easy way of understanding everything about their architecture. Teams help organizations improve service quality while fostering a sense ownership and pride. Scaffolder allows developers to scaffold a new service using templates created by your team in less than five minute.

GitLab is a complete DevOps platform. GitLab gives you a complete CI/CD toolchain right out of the box. One interface. One conversation. One permission model. GitLab is a complete DevOps platform, delivered in one application. It fundamentally changes the way Security, Development, and Ops teams collaborate. GitLab reduces development time and costs, reduces application vulnerabilities, and speeds up software delivery. It also increases developer productivity. Source code management allows for collaboration, sharing, and coordination across the entire software development team. To accelerate software delivery, track and merge branches, audit changes, and enable concurrent work. Code can be reviewed, discussed, shared knowledge, and identified defects among distributed teams through asynchronous review. Automate, track, and report code reviews.

Guru is an AI search and knowledge platform that delivers trusted information from your company's scattered docs, apps, and chats the moment you need it without leaving the apps you’re already in. No need to dig for information, Guru’s personalized AI assistant gets you verified/trusted, relevant answers. Guru's AI can turn those answers into an AI-powered knowledge platform to replace your legacy wiki and intranet too. Guru natively integrates with Slack, Google, Microsoft Sharepoint, OneDrive, and Teams, Salesforce, Zendesk, Atlassian Confluence, Atlassian Jira, Dropbox, Box, Google Drive, Asana, HubSpot, ClickUp, GitHub, GitLab, Intercom, ServiceNow, Linear, Front, and more

Sogolytics, an experience management platform, allows companies to collect, analyze and use employee and customer data to drive business growth. Sogolytics is used by organizations across all industries to track interactions at all touchpoints with customers and employees. The best-in-class reporting delivers real-time, actionable insights that help to prevent and mitigate potential problems. SogoCX improves every aspect of a company's customer experience. This means improved conversion rates, simplified data management, and understanding customers to increase return on investment. Organizations can use SogoCX to measure key metrics like NPS, CSAT and CES. SogoEX software is used by organizations to collect and use data to improve engagement and reduce turnover. This platform allows HR and leadership to drive organizational changes through real-time feedback collection and employee engagement.

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

CallTrackingMetrics is the only SaaS platform that uses call tracking and conversion intelligence to inform contact center automation--resulting in a more personalized customer experience. Find out which marketing campaigns are generating leads or conversions and use that data for automated call flows and to power your contact centre. Our phone, text, online, and live chat tools allow you to unify communications across your organization. CallTrackingMetrics is trusted by more than 100,000 users worldwide to manage communications for their sales, marketing, and service teams. Call tracking features include reliable dynamic numbers insertion (DNI), for session-level attribution, local and toll-free tracking numbers, and omnichannelattribution across calls, texts and form fills. Contact center features include a browser-based softphone and smart routing options.

Global App Testing (GAT) allows tech teams to test in over 189 countries with over 60,000+ professional testers who use real devices and environments. Enhance your testing process and increase release quality and speed whilst improving budget efficiency via the GAT platform, which is fully integrated to work seamlessly with your existing DevOps or CI/CD tools. Whether you are looking for full time QA support, or to manage spikes in your release cycles, the GAT integration-led approach empowers you to manage your entire testing workflow from test launch to results analysis without leaving your existing tooling (such as Github, Jira, Testrail etc). Through our integrated platform, we enable unscripted exploratory testing and scripted functional test case execution to be embedded within your CI/CD and SDLC processes, providing the perfect synergy with your automation testing tools. Test results are returned in real time. Start receiving results in as little as 15 minutes with a full bug report delivered within a few hours, enabling quick feedback on critical issues and edge cases.

DataBahn is an advanced platform that harnesses the power of AI to manage data pipelines and enhance security, streamlining the processes of data collection, integration, and optimization from a variety of sources to various destinations. Boasting a robust array of over 400 connectors, it simplifies the onboarding process and boosts the efficiency of data flow significantly. The platform automates data collection and ingestion, allowing for smooth integration, even when dealing with disparate security tools. Moreover, it optimizes costs related to SIEM and data storage through intelligent, rule-based filtering, which directs less critical data to more affordable storage options. It also ensures real-time visibility and insights by utilizing telemetry health alerts and implementing failover handling, which guarantees the integrity and completeness of data collection. Comprehensive data governance is further supported by AI-driven tagging, automated quarantining of sensitive information, and mechanisms in place to prevent vendor lock-in. In addition, DataBahn's adaptability allows organizations to stay agile and responsive to evolving data management needs.