Software/ platforms

Faros AI expands its Engineering Intelligence Platform

New ‘Asimov’ release measures the ROI of AI-powered coding assistants, generates org-wide heatmaps and health panels, and weaves AI into daily engineering operations

Faros AI, the complete software engineering intelligence platform, today announced a major platform expansion with the Faros AI ‘Asimov’ release. Asimov is built to help organizations maximize the effectiveness and efficiency of the engineering workforce, at a time of reduced operating budgets and the emergence of AI-powered coding assistants.

The latest version of Faros’s extensible AI-native platform includes new EngOps modules focused on maximizing return on engineering budgets, at-a-glance organizational heatmaps for strategic KPIs, and AI‑assisted engineering data analysis and data-driven workflow automation. Designed to maximize the productivity of human and AI-powered engineering, these new capabilities further strengthen engineering’s collaboration with critical partners in finance, human resources, and product & program management.

“With the explosion of AI and digitization of everything, software is now the business,” said Vitaly Gordon, CEO & Co-Founder of Faros AI. “The expanded Faros AI platform gives our customers the ability to make every part of the software engineering ecosystem work together at the greatest level of efficiency with the highest levels of value creation.”

Maximizing return on engineering budgets

As boards increase their scrutiny, Faros AI helps engineering leaders demonstrate rigor in budget allocation with out-of-the-box analytics and reporting across disparate data sources to accurately assess business impact and ROI of initiatives, technology, people, and platforms, with these new EngOps modules:

AI Transformation helps engineering organizations navigate critical decisions around the adoption of AI-powered technologies like GitHub Copilot within the software engineering discipline. Since most organizations choose to begin with a small-scale pilot, this module calculates the time savings and economic impact of pilot participants through a combination of systems and developer surveys and tracks the potential downstream benefits from wider adoption.

“As an engineering leader, Faros can help me understand how our engineers are using GitHub Copilot, the value they are getting from it, and where we can strategically improve productivity by enhancing certain developer workflows,” said Mustafa Furniturewala, SVP of Engineering at Coursera, an early adopter of GitHub Copilot and Faros’s AI Transformation EngOps module. “The data and insights will help us improve training for our teams, while also enabling developers to understand how AI augmentation is impacting their own productivity.”

Initiative Tracking allows engineering leaders and their product and business partners to ensure engineering is appropriately staffed and working on the right priorities to achieve business outcomes. The Initiative Tracking module replaces manual reporting and subjective updates with real-time visibility into initiative progress and budget utilization to help minimize cost overruns and inform capacity allocations.

Developer Experience centralizes developer satisfaction survey data in one place and intersects the sentiment data from employee responses with telemetry-based data from engineering operations. This novel blended visibility into the complete developer experience provides actionable insights that allow the organization to take corrective measures faster and observe their impact on engagement, retention, and operational excellence over time.

Reducing risk to business outcomes with heatmaps and health panels

Executive leadership needs to be able to track the most important metrics across engineering at a glance, to quickly identify important signals without having to wade through a pile of data.

“The visibility in Faros helps raise red flags and inform us if something is off in the way we are staffing the teams,” said Vineeta Puranik, SVP Engineering and Operations at SmartBear. “We adjust our resources very quickly and efficiently based on those signals.”

Faros AI now provides role-based intuitive views that create an instant visual understanding of areas requiring attention.

Scorecard provides a visual heatmap of cross-organizational performance against the metrics that matter most. This powerful birds-eye view creates top-down alignment — from CTOs to Directors — allowing senior leaders to instantly gauge their organization’s health across multiple dimensions of business outcomes and quickly hone in on areas of concern.

TeamCentral is a new dashboard for engineering managers to monitor the health and progress of their teams. Instead of checking multiple tools and dashboards, this single page collects everything a manager needs to know, including speed, quality, predictability and sentiment metrics and essential operational data like who’s on call and what the team is actively working on.

Accelerating the transition to data-driven engineering with Lighthouse AI

Expanding upon the launch of Lighthouse AI in June, 2023, the latest Asimov release includes:

Questions supercharge engineering data analysis, helping easily and quickly translate business questions into queries and charts on data stored in Faros. Based on a natural language prompt, Lighthouse AI suggests related charts and tables that will assist with context-specific decision-making, problem-solving, and performance tracking.

Explanations accelerate the widespread adoption of data in day-to-day engineering operations. Every Faros AI chart, whether custom-built or out-of-the-box now features an natural language chart explainer that helps laypersons understand metrics better and act on them more confidently.

Automations increase engineering efficiency by automating repetitive tasks that are either burdensome or easy to forget. Partnering with industry-leading workflow automation tool n8n, Faros offers drag-and-drop multi-step workflows with 220+ ready-to-use endpoints to help organizations efficiently do the right things, for example, alerting owners via Slack or PagerDuty when a metric breaches an accepted threshold or sending a bi-weekly email summary of recently released features to leadership.

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