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Forward Networks launches Forward AI for network operations Using digital twin technology. Forward Networks, the industry leader in network digital twin technology, announced Forward AI, a new capability that accelerates network operations by enabling network, security, and cloud teams to ask complex questions, understand network behavior, validate outcomes and safely automate workflows with confidence. Built on a mathematically accurate digital twin of the network, Forward AI allows IT teams and AI agents to act on trusted data rather than assumptions. Forward AI brings mathematical certainty to agentic operations. Using trusted data, the conversational system enables network, security, and cloud teams to ask complex questions, understand network behavior, validate outcomes, and safely automate workflows with confidence. Every recommendation and action is delivered with full transparency, including the reasoning and evidence for each step. This is how AI becomes a trusted operator at scale. As IT organizations accelerate AI adoption and modernization, network complexity is increasing while headcount remains largely flat, placing new pressure on teams to sustain reliability and security at scale. AI-driven operations offer a path forward, but require accurate, complete, and verifiable data. Forward AI is led by co-founder Nikhil Handigol, who was recently appointed Chief AI Officer. Over more than a decade, Handigol has designed mathematically grounded systems for large-scale network operations and has played a central role in shaping Forward's digital twin architecture from its inception. He is a named co-inventor on eight patents related to network analysis and network monitoring. Forward AI establishes a foundation for the safe adoption of agentic AI in network operations by delivering validated, evidence-backed recommendations. Built on a complete, behaviorally accurate understanding of the network, Forward AI enables agentic workflows that IT teams can trust. Each result is accompanied by clear evidence, allowing teams to inspect underlying data and reasoning, validate outcomes, and act with confidence. Forward Networks is extending trusted agentic AI beyond its own platform. Through support for the Model Context Protocol (MCP), Forward AI makes its verification foundation available to enterprises and third-party developers, enabling them to build agentic tools that deliver trustworthy outcomes grounded in accurate, always current network data. Forward AI will be included in the Forward Enterprise platform. The capability is scheduled for general availability in April 2026. David Erickson, CEO and co-founder, Forward Networks When The Fast Mode founded Forward Networks, The Fast Mode started with a simple but strategic question: does the network actually behave as intended, by design, in production, and across changes. Answering that question requires more than visibility. It requires a mathematically accurate model of the network itself. That foundation is what Forward Enterprise delivers. Forward AI builds on it to fundamentally expand what's possible, allowing enterprises to safely reason about their networks, validate outcomes, and take action with confidence. This is how AI becomes a trusted part of operating critical infrastructure. Nikhil Handigol, co-founder and chief AI officer, Forward Networks Forward Enterprise is already trusted by organizations running some of the largest and most complex networks in the world. That experience has given The Fast Mode a first-hand view into the operational challenges that matter most, and into where human error and uncertainty still limit confidence and scale. Forward AI builds on those learnings by extending the power of a mathematically accurate digital twin across operations, enabling organizations to safely adopt AI-driven workflows, reason transparently about outcomes, and preserve the safeguards required to operate critical infrastructure. Before Forward, getting accurate network information meant spreadsheets, tribal knowledge, and a lot of guesswork. Forward gave The Fast Mode a trusted view of current and future network state. Forward AI takes that further by making that truth accessible to everyone on the operations team through simple, natural-language questions. It dramatically lowers the barrier to insight and makes Forward an indispensable partner in how The Fast Mode run its network. Because Forward Enterprise delivers comprehensive, domain-specific network data for heterogeneous environments, it is well positioned to take advantage of agentic capabilities. Forward AI strengthens trust in AI by providing full transparency into how recommendations are generated. Exposing the reasoning behind AI-driven actions, keeps humans in the loop, builds confidence, and ultimately improves operational efficiency. RESEARCH INSIGHTS Advancing Network Management with GenAI The Role of DPI-driven Traffic Intelligence Ray Sharma is an Industry Analyst and Editor at The Fast Mode. He has over 15 years of experience in mobile broadband technologies and solutions, conducting research and analysis on various technology segments and producing articles and write-ups on the latest developments within the sector. He is also in charge of social media engagement and industry liaisons.

Forward Networks launches digital twin, hails mobile operator success. Forward Networks says it is taking operators forward with digital twin technology that will advance agentic AI use cases in the network. A company specialising in digital twin technology has told TMN that it has helped one mobile operator save outage costs, increase speed of deployment and reduce downtime by applying its technology to live network operations. Forward Networks, which has today announced Forward AI, said that its technology gives operations teams the ability to ask complex questions and validate outcomes of automated processes in natural language by accessing a "mathematically accurate" digital twin of the network built on "trusted data". Forward AI will be included in the company's Forward Enterprise platform and is scheduled for general availability in April 2026. Operator outcomes. Although the company was not able to name the operators that gained results, TMN understands Forward Networks has had engagements with Vodafone and Verizon, amongst others. A spokesperson told The Mobile Network, "One mobile operator accelerated its deployment velocity by 70% and reduce unplanned downtime by 33%. In another testament to the benefits of a network digital twin for telecom operators, a Forward Networks customer calculated $11M in savings by increasing the efficiency and eliminating outages related to change management and automation only." "When we founded Forward Networks, we started with a simple but strategic question: does the network actually behave as intended, by design, in production, and across changes," said David Erickson, CEO and co-founder of Forward Networks. "Answering that question requires more than visibility. It requires a mathematically accurate model of the network itself. "That is what Forward Enterprise delivers. Forward AI builds on that foundation to allow enterprises to reason about their networks, validate outcomes, and take action with confidence." Nikhil Handigol, co-founder and chief AI officer at Forward Networks said, "Forward AI extends the power of a mathematically accurate digital twin across operations, enabling organisations to safely adopt AI-driven workflows, reason transparently about outcomes, and preserve the safeguards required to operate critical infrastructure." Forward AI says that by creating a behaviorally accurate understanding of the network the digital twin model establishes a foundation for the safe adoption of agentic AI in network operations, delivering validated, evidence-backed recommendations. The company added that it would support the Model Context Protocol (MCP), making its verification foundation available to enterprises and third-party developers, enabling them to build agentic tools grounded in accurate, current network data. "This is how AI becomes a trusted part of operating critical infrastructure," Erickson said. The contextualisation and validation of data, application of knowledge graphs and digital twin capabilities are seen as key to the introduction of advanced AI and agentic AI capabilities in network operations. Most operators are grappling with how to advance in this area, seeing potential efficiency and monetisation benefits. A blog post from Forward Networks' Nikhil Handigol, Co-Founder, claimed: "Forward AI is not just another thin wrapper around an LLM. It is a conversational agentic system designed to plan, reason, and execute multi-step workflows using mathematically validated network data, built natively on the industry's first mathematically accurate network digital twin. While general-purpose AI often relies on assumptions, Forward AI acts on trusted data. "When you submit a prompt, Forward AI doesn't approximate an answer based on assumptions or partial context. Instead, it constructs an execution plan, performs deep network analysis, and produces results accompanied by clear explanations of the underlying reasoning. Every outcome is derived from domain-specific evidence, allowing operators to understand not just what the answer is, but why it is correct."

Forward Networks has introduced Forward AI, a new capability built on its network digital twin technology that enables IT teams to query complex network operations through natural language. The system provides mathematically verified answers and recommendations, allowing organisations to validate outcomes and automate workflows with confidence. The company appointed co-founder Nikhil Handigol as Chief AI Officer to lead the initiative. Forward AI aims to address growing network complexity whilst maintaining accuracy through its digital twin foundation, which creates a mathematically precise model of production networks. The capability will be included in the Forward Enterprise platform and is scheduled for general availability in April 2026. Forward Networks supports major clients including Goldman Sachs, PayPal, and IBM across multi-vendor environments and major cloud platforms.