Future Techly

Social engineering is the breach nobody sees coming Attackers don’t need zero-days when humans are the easier exploit. The human layer is finally getting real defense. 🚀 Humanix Raises $18M To Stop Social Engineering At The Source San Francisco–based Humanix closed $18M across Seed + Series A to build AI-powered defenses for live conversations, service desks, and customer-facing channels. 🔹 Lead Investor (Series A): Acrew Capital 🔹 Lead Investor (Seed): boldstart ventures 🔹 Total Raised: $18M Founder & CEO: – Keith Stewart What They’re Building: Humanix uses behavioral research–driven AI to detect manipulation tactics during live interactions and guide employees in real time. What the platform delivers: 🧠 AI detection of social engineering during conversations ⚡ Instant intervention and response guidance 📜 Verified compliance and process assurance 🏦 Adoption across finance, hospitality, and critical service industries Why This Matters: Most cybersecurity tools guard infrastructure. Humanix guards people. The attack surface has shifted, and this is one of the few platforms treating humans like part of the system instead of an afterthought. What The Funding Fuels: – Expansion of engineering and product – Deeper behavioral AI research – Scaling deployments across service-heavy industries My Take: Companies keep losing millions to a polite phone call. Humanix is the rare team combining behavioral science and AI tightly enough to make social engineering detection reliable, not reactive. Follow Future Techly for high-signal breakdowns across AI, security, and enterprise workflows. P.S. Repost so operators and security teams stop pretending “awareness training” is a real defense. -------- Graphic Created By Muhammad Asad

Cloud bills shouldn’t punish good engineering Most teams ship features fast and pay for it later in compute waste. Code-level cost intelligence fixes that imbalance. 🚀 Frugal AI Raises $5M Seed To Turn Inefficient Code Into Cloud Savings Ottawa-based Frugal AI secured a $5M Seed round to scale its Application Cost Engineering platform. 🔹 Lead Investor: Whitecap Venture Partners 🔹 Participants: Mistral Venture Partners, founders of Snyk and CloudCheckr 🔹 Total Raised: $5M Founders: – Mike Weider – Craig Conboy – Rob Calendino What They’re Building Frugal AI built an ACE platform that analyzes source code, observability data, and cloud bills to flag expensive patterns and auto-generate quality-assured pull requests that cut cloud spend without slowing development. What it unlocks: 💸 Code-level cloud savings ⚙️ PR-ready optimizations 📊 Deep integration with observability and billing data ☁️ Support for AWS, GCP, Datadog, New Relic, Anthropic, OpenAI (Azure coming) Why This Matters: Cloud costs are rarely a billing problem. They’re a code problem teams don’t see. Frugal AI shifts cost engineering into the development loop instead of finance cleanup mode. What The Funding Fuels: – Scaling engineering and product – Expanding integrations – Commercial launch planned for Q1 2026 My Take Teams brag about velocity, then quietly panic at the cloud bill. Frugal AI gives engineering the cost observability it’s been missing. Code-level optimization is where real savings compound. Follow Future Techly for clear, signal-dense funding breakdowns across AI, devtools, and cloud infrastructure. P.S. Repost so founders and engineering leaders see where cloud efficiency is heading next. -------- Graphic Created By Muhammad Asad

Regulatory chaos is slowing MedTech innovation Most device teams drown in compliance work before they ever touch a patient outcome. This is where infrastructure matters. 🚀 Quality Means Business Raises $2M Seed To Build MedTech’s Regulatory Intelligence Layer Boston-based Quality Means Business (QMB) closed a $2M Seed round to accelerate its AI-driven RegTech platform for MedTech manufacturers. 🔹 Lead Investors: The Boston Foundation’s Business Equity Investment Fund, CEI VENTURES, INC. 🔹 Total Raised: $2M Governance: – Michel E. Moravia, MBA, MSE, Chairman & CEO – Orlando Watkins, Board Director – Robert Bennett, Board Director – Shannon Bean, MS, Board Observer What They’re Building QMB created QualiVerse, a regulatory intelligence engine designed for MedTech quality, regulatory, and new product development. The platform combines AI copilots, predictive analytics, and compliance-aware automation so innovators can ship devices without drowning in documentation debt. What it unlocks: 📊 Automated regulatory workflows ⚙️ Compliance-aware decision support 🔍 Predictive quality intelligence 🏥 Faster, safer MedTech launches Why This Matters: Regulatory complexity is one of the biggest barriers to MedTech innovation. Teams waste months interpreting standards instead of improving patient outcomes. QMB turns that overhead into infrastructure. What The Funding Fuels: – Engineering expansion – Deeper data integrations – RegTech-as-Infrastructure pilots with MedTech manufacturers into late 2025 My Take: MedTech doesn’t need more dashboards. It needs infrastructure that understands regulations as deeply as engineers do. QMB is rewriting the regulatory stack so the next generation of devices can move faster without cutting corners. Follow Future Techly for sharp, signal-first breakdowns across healthtech, regulated industries, and AI infrastructure. P.S. Repost so more founders see the shift toward compliance automation. --------- Graphic Created By Muhammad Asad

Incidents shouldn’t take hours to untangle Modern systems break in ways dashboards can’t explain. Teams need reasoning, not more charts. 🚀 Deductive AI Raises $7.5M Seed To Build AI SRE Agents Mountain View–based Deductive AI secured a $7.5M Seed round to push incident response toward autonomous, evidence-driven resolution. 🔹 Lead Investor: CRV 🔹 Participants: Databricks Ventures, Thomvest Ventures, PrimeSet 🔹 Total Raised: $7.5M Founders: – Sameer Agarwal, Co-founder & CTO – Rakesh Kothari, Co-founder & CEO What They’re Building Deductive AI is developing AI SRE agents that connect codebases and telemetry to guide teams from detection to root cause. Their system anchors itself in a constantly updated knowledge graph mapping the relationships between services, components, and events. What it unlocks: ⚡ Root-cause pinpointing in seconds 📡 Unified view across logs, metrics, traces, and code 🧠 Agents that test hypotheses and evaluate evidence 🔐 A deployable platform for training incident-resolution agents Why This Matters Downtime still burns money because engineers sift through fragmented signals. Deductive AI compresses that search by letting agents reason through the system graph directly. What The Funding Fuels – Expansion of engineering and platform capabilities – Deeper development of the AI SRE agent stack – Scaling GTM for enterprise operations teams My Take Observability created visibility, not understanding. Deductive AI is building the layer that reasons over the chaos, which is why it fits neatly into the future of automated ops. Follow Future Techly for concise, signal-dense breakdowns in AI, infrastructure, and real-world systems. P.S. Repost so more engineering teams see where incident response is headed. ------- Graphic Created By Muhammad Asad

Enterprise analytics just got a new center of gravity Static dashboards are relics. Autonomous data intelligence is the shift everyone’s been waiting for. 🚀 WisdomAI Raises $50M Series A To Build The AI Data Analyst San Francisco–based WisdomAI closed a $50M Series A, bringing total funding to $73M, as it pushes enterprise analytics into a proactive, agent-driven era. 🔹 Lead Investor: Kleiner Perkins 🔹 New Investor: NVentures (NVIDIA) 🔹 Participants: Coatue Management, Latitude Capital, Madrona, GTM Capital, Menlo Ventures, U First Capital 🔹 Total Raised: $73M Founder & CEO: – Soham Mazumdar What They’re Building: WisdomAI is creating an AI Data Analyst that moves enterprises beyond passive BI. Their system layers autonomous reasoning over structured, semi-structured, and unstructured data, delivering real-time insights across every workflow. What it unlocks: 📊 Conversational analytics at enterprise scale ⚡ Proactive, context-aware insights 🔍 Unified intelligence through the Enterprise Context Layer 🏢 Deployment across tech, healthcare, finance, energy, and manufacturing Why This Matters: Enterprises still rely on dashboards that require humans to chase down answers. WisdomAI flips the model by pushing insights before teams need them, removing latency from decision-making. What The Funding Fuels: – Expansion of engineering and product teams – Acceleration of the AI Data Analyst roadmap – Scaling global go-to-market operations My Take: Every enterprise wants “AI-driven insights,” but most are stitched together with dashboards and wishful thinking. WisdomAI rebuilt the analytics stack around autonomous agents, not visualizations. That’s why Fortune 500s are already leaning in. Follow Future Techly for tight, high-signal breakdowns across AI, enterprise tech, and infrastructure. P.S. Repost to help founders and data teams see where analytics is heading next. -------- Graphic Created By Muhammad Asad

Customer success isn’t broken. It’s blind. OnRamp is trying to give onboarding the intelligence it should have had years ago. 🚀 OnRamp Raises $15M Series A To Build AI-Powered Customer Onboarding & Engagement Boston-based OnRamp completed its $15M Series A, aiming to turn onboarding from a chaotic spreadsheet ritual into a predictable revenue engine. 🔹 Lead Investor: Koch Disruptive Technologies (KDT) 🔹 Participants: Contour Venture Partners, Javelin Venture Partners, Pear VC, and others Founders: – Paul Holder – Ross Lerner What OnRamp Does: OnRamp provides an AI-enabled onboarding and engagement platform designed to help companies accelerate product adoption, strengthen long-term relationships, and unlock revenue expansion. It automates workflows that guide users from first touch to full value realization. Teams use it to: – Reduce churn – Speed up time-to-value – Accelerate revenue realization Why This Matters: Most companies overinvest in acquisition and underinvest in activation. The real revenue leak isn’t top-of-funnel — it’s the onboarding that never lands. What the Funding Fuels: – AI capability expansion – Team scaling – A new 6,000 sq. ft. Boston office opening in early 2026 My Take: AI-native onboarding is becoming a mandatory layer for SaaS companies hitting scale. OnRamp is positioning itself as the operating system for post-sale growth. Follow Future Techly for sharp coverage on AI platforms, SaaS ops, and customer lifecycle innovation. P.S. Repost to move this insight deeper into the customer success ecosystem. -------- Graphic Created By Muhammad Asad

Legal decisions aren’t mysterious. They’re patterns waiting to be modeled. Theo Ai is pushing the legal world toward data-driven judgment. ⚖️ Theo Ai Raises $10M+ To Build Predictive Intelligence For Am Law 200 & Enterprise GCs Palo Alto-based Theo Ai has secured over $10M in total funding, expanding its mission to bring outcome prediction and actionable analytics to the legal industry. 🔹 Lead Investor: Run Ventures 🔹 Board Addition: Porntepp U. (Partner, Run Ventures) Founder & CEO: – Patrick Ip What Theo Ai Does: Theo Ai provides an AI-driven predictive engine that forecasts litigation outcomes with models trained on historical case data, real-time analytics, and deep legal domain expertise. Its platform gives Am Law firms and enterprise GCs a probability model to guide strategy, cost decisions, negotiation posture, and case prioritization. Why This Matters: Legal risk is usually managed with experience and intuition. Predictive modeling introduces quantifiable foresight. The firms that adopt it first will operate with a strategic edge others can’t replicate. What the Funding Fuels: – Expansion of AI capabilities – Hiring engineering talent – Continued development of its predictive analytics platform – Scaling enterprise deployments across legal teams Advisory Strength: Theo Ai announced a General Counsel Advisory Board featuring senior legal leaders from Bristol Myers Squibb, Docusign, GoDaddy, HP, US Bank, SentinelOne, Regal, eBay, and more. This gives the company direct insight into legal operations at scale. My Take: Litigation prediction will become a core system-of-intelligence for modern legal teams. Theo Ai is positioning itself as the operating layer that turns legal data into strategic advantage. Follow Future Techly for sharp analysis on AI, enterprise decision systems, and the future of legal tech. P.S. Repost to circulate this insight across the legal innovation community. -------- Graphic Created By Muhammad Asad

AI agents won’t matter unless they feel human. Tavus is trying to cross that line with emotional intelligence baked into the model stack. 🚀 Tavus Raises $40M To Build Agentic AI Humans With Real Emotional Presence San Francisco–based Tavus secured $40M in Series B funding to push its next wave of human-computing systems. 🔹 Lead Investor: CRV 🔹 Participants: Scale Venture Partners, Sequoia Capital, Y Combinator, HubSpot Ventures, Flex Capital Founder & CEO: – Hassaan Raza What They’re Building: Tavus is developing PALs (Personal Affective Links) — agentic AI humans designed to see, understand, express, and interact across text, voice, and face-to-face video with emotional intelligence and adaptive reasoning. The stack is driven by three in-house foundational models: 🎭 Phoenix-4 State-of-the-art rendering with controlled expression, head pose, and emotion at conversational latency. 🔊 Sparrow-1 Audio-understanding and conversational-intelligence engine that adapts tone, timing, and intent in real time. 👁️ Raven-1 Perception model interpreting context, environments, emotions, gestures, and people. Paired with Tavus’s orchestration and memory systems, PALs operate as multimodal, emotionally aware, agentic video-first AI humans. Why This Matters: Most “AI agents” today feel like scripted chat apps wearing fancy clothes. Tavus is rebuilding the sensory stack so agents can actually see, feel, and respond with human-like nuance. What the Funding Fuels: – Scaling R&D – Expanding product capabilities – Strengthening the infrastructure behind real-time, emotionally adaptive AI humans My Take: Everyone says they’re building “AI agents.” Tavus is one of the few building the sensory and emotional primitives required to make them feel real, not robotic. Follow Future Techly for sharp breakdowns across applied AI, agentic systems, and frontier model architectures. P.S. Repost so more founders and teams catch the next wave of human-computing tech. -------- Graphic Created By Muhammad Asad

Specialty meds shouldn’t require a scavenger hunt. House Rx is rebuilding the model inside the clinic. 🚀 House Rx Raises $55M To Scale Medically-Integrated Specialty Pharmacies San Francisco–based House Rx secured $55M Series B to expand its in-clinic specialty pharmacy model, giving patients direct access to high-touch medication support where they already receive care. 🔹 Lead Investors: New Enterprise Associates (NEA), Town Hall Ventures 🔹 Participants: LRVHealth, First Round Capital, Bessemer Venture Partners, Silicon Valley Bank 🔹 Total Raised: $100M Founder & CEO: – Ogi Kavazovic What They’re Building: House Rx helps clinics operate in-house specialty pharmacies that weave pharmacist expertise directly into patient care. Their model delivers: 🏥 Medically integrated dispensing inside the clinic 📉 Lower costs and better medication access 🤝 Stronger provider-pharmacist coordination 📊 Tech-enabled workflows that raise adherence and outcomes They’ve already partnered with 1,000+ providers across 80 clinics, processing $1.5B in specialty scripts annually, on track to hit $3B by 2026. Why This Matters: Specialty meds are where outcomes and costs collide. When the pharmacy sits outside the clinic, patients carry the burden. Integrating it back into care fixes the break in the system. What the Funding Fuels: – Expansion of the in-clinic pharmacy model nationwide – Deeper tech automation across prescribing and dispensing – Strengthening outcomes tracking and provider workflows My Take: Most pharmacy innovation happens around the edges. House Rx moved the whole pharmacy inside the care team, which is why the economics and outcomes both shift. Follow Future Techly for clear, signal-dense breakdowns across healthtech, AI, and real-world infrastructure. P.S. Repost so more founders and teams see where integrated care is heading next. --------- Graphic Created By Muhammad Asad

Corporate events shouldn’t drain entire teams. BoomPop is turning the pain into a workflow. 🚀 BoomPop Raises $41M To Bring AI-Native Automation To Company Events San Francisco-based BoomPop secured $41M to expand deeper into corporate group travel and events, including $16M in debt and credit from SVB. 🔹 Lead Investor: Wing Venture Capital 🔹 Participants: Atomic, ACME Capital, Zypsy, Four Rivers, Thayer Investment Partners, FOG Ventures, Gaingels 🔹 Notable Angels: Alex Rodriguez, Brian O’Malley, Dane Glasgow, Christopher Payne, and multiple Silicon Valley operators Founders: – Healey Cypher – Blake Hudelson What They’re Building: BoomPop delivers an AI-powered event platform built for both seasoned planners and the poor souls drafted into planning by accident. The platform automates: 📍 Destination discovery 📅 Itinerary creation 🖥️ Guest-facing websites 🤝 Vendor sourcing and booking 📨 RSVPs and guest coordination 💬 24/7 AI support via Slack or text Its AI analyzes real-world signals in real time: ☁️ Weather 🏨 Hotel + venue pricing ✈️ Flight availability 📊 Local events (SXSW, Dreamforce, etc.) 📚 Past itineraries …then generates end-to-end event options and runs execution automatically. BoomPop has already powered 60,000+ hotel nights for clients like Google, Dick’s Sporting Goods, Tesa, Bill.com, Forrester, and SVB. Why This Matters: Event planning is a costly time sink. Corporations treat it like a logistical afterthought. Automating the entire pipeline converts chaos into a predictable system. What the Funding Fuels: – Expansion into corporate travel + large-scale events – Full rollout of its AI-native planning OS – Product development for enterprise workflows My Take: Most event tools digitize checklists. BoomPop is absorbing the entire job description and handing planners a real co-pilot. Follow Future Techly for sharp, architecture-level analysis across AI, software, and real-world automation. P.S. Repost so ops teams finally see what fully automated events can look like. -------- Graphic Created By Muhammad Asad