DevRev

Only 9% of employees trust AI for decisions that actually matter. Nine. Those AI tools and models work in the demo. But the team isn't using them. 54% bypassed AI last month and did the work manually. Enterprises are losing 51 workdays per employee per year to this friction. And smarter models have just made it worse. They produce answers that "sound" right… But they're wrong. More confidence. Same hallucinations. So the real question isn't "does this AI work?" It's "how do I know my team will trust the next thing I buy?" We built the answer layer to hold up under audit. Precision as the starting point – not the promise. Computer doesn't guess. It understands what your data means, before the model ever sees the question. Entity resolution. Field-level annotation. Relationship mapping across systems. All kept fresh through Computer AirSync, our patented two-way sync engine. The result? Answers that are relevant, accurate, and complete – because the system already knows. Same question. Two people. Two completely different answers. Both dead right. Your AE sees renewal risk. Your engineer sees the error log. Same truth – right lens. Ask Monday. Rephrase Thursday. Same number. No contradictions. No silent failures. The model is the commodity. The understanding layer is the advantage. Precision is the outcome. Link in comments for you to know more about why this matters.

Some of you are starting your Friday. Some are wrapping it up. Either way, there's always that one phrase that turns a simple day into an unexpected adventure. Which one gets your vote?

Your new team joined last week. Your AI still has no idea who they are. The data is there. Fields are populated, objects exist. But to your AI, it's a spreadsheet with no headers. Without annotations – the context layer that tells AI what things mean, not just where they are - nothing is searchable, nothing is useful. And here's the part that burns: this isn't a one-time setup problem. Annotations decay. Silently. Teams evolve, fields get added, and the context that made your AI sharp six months ago slowly drifts from reality. You don't notice until the answers start feeling slightly off. By then, you're buried in debt you didn't know you were taking on. Ahmed Bashir and Anirudh Shenoy are ripping this open live tonight – taking a real team from zero context to a working knowledge layer, start to finish. 📅 May 28th | 8:30 PM IST | DevRev Live Set a reminder: https://bit.ly/4tXzRmj

A week ago we got senior CX leaders across Melbourne, Sydney and Auckland in a room and asked who's approved an AI investment recently. Every hand up. However, when we asked “Who can articulate the ROI?” Radio silence. That gap is the whole story right now. The demos are easy to love. Summarisation, classification – hardly twelve seconds and you're sold. But the real question was never whether agents can act. It's whether they can act precisely, safely, and without blowing your token budget in a regulated environment. That's where the conversation gets honest. Structured memory that cuts token usage by 95% – so the agent gets the right data, not all the data. Governance where someone owns it when an agent misbehaves at scale. And the discipline to start with one napkin-sized problem, not ten. Precise enough to act. Safe enough to trust. Efficient enough to scale. That's the bar now. Richard Marr Sunil Mahale Ahmed Bashir Pratik Shanbhag Michael Robinson Jeff Smith Tom Davies

Wouldn’t it be better if your AI remembered you? Computer is the only AI with Shared Memory. Which means it’s the only AI with a memory that grows – and grows. Most AIs can’t even remember yesterday. Like... at all. You spent 20 minutes giving it context. It gave you something great. You closed the tab, the laptop. Then came back today and it looked at you like a stranger. Every team we talked to said the same thing – “it’s smart, but it doesn’t know us.” And how could it? Your sales team lives in the CRM. Engineering in Jira. Product in Confluence. None of these talk to each other. Every day, people waste hours hunting for info that already exists... somewhere. That’s the “Groundhog Day Dilemma”. Every question, every damn time, your AI starts from scratch. That’s why we designed Computer as the only AI with native Shared Memory. It remembers everything. Your structured data. The human interactions no CRM captures. How your teams actually think and work – that’s the source of every precise, efficient answer. Other AIs forget, and guess. Computer remembers, and knows. Read more: https://ow.ly/Wh4k50Z44VE

What do commanding 75,000 military personnel across the globe and building enterprise AI have in common? Discipline. Accountability. An understanding of scale. Clarity of mission. We’re honored to welcome General Richard “Rich” Clarke, U.S. Army (Retired), to DevRev’s Board of Directors. General Clarke most recently served as Commander of U.S. Special Operations Command (USSOCOM). With an annual operating budget of over $25 billion, he reported directly to the Secretary of Defense. As we scale Computer globally, General Richard Clarke's experience building and leading organizations at unprecedented scale is exactly the kind of experience, perspective, and grit we know will help sharpen our edge. Full announcement: bit.ly/4f31xCH The mission continues.

🔊 Today is “Computer, upgraded” day. And it’s a big day. Here’s what you’re going to love about the new Computer: 1. Native “Shared Memory” Other AIs forget, and guess. As the only AI with native Shared Memory, Computer remembers, and knows. Your docs, your deals, the human interactions no CRM captures – all of it. 2. Precise, trusted answers Answers that get better. And better. And... you get the idea. Day 1, impressive. Day 90, extraordinary. 3. Multiplayer mode Shared sessions – not separate briefings. Instant collaboration – not diary tennis. Full context – not “can you catch me up.” Just @Computer and it’s in the room with you. 4. Agent Studio + proven skills Build agents in plain language. Test before they touch anything real. Scale what works. 5. Safe actions Computer takes action – within boundaries you set. Human approval. Full visibility. Rollback built in. Which is why, unlike other AIs, Computer sometimes says “no.” That’s just a taster. To get all the details, read our launch blog: link in comments

30 rows per second. 1.3 billion row dataset. Load time measured in weeks. That's what happens when your AI tries to bulk-copy a data warehouse. The alternative? Re-explore the schema from scratch every query. Also broken. We built a third option: the AI indexes your schema once, runs jobs on a schedule, and queries on demand. Your data stays exactly where it is. Ahmed Bashir + Jonathan Hodges are showing exactly how this works – live, on real Snowflake and Fabric datasets: https://bit.ly/3PDkwt3 📅 Tomorrow | May 21st | 8:30 PM IST | DevRev Live

AI models have become smarter. But the enterprise hasn't become more connected. Our CEO and Co-founder Dheeraj Pandey recently sat down with NYSE "Floor Talk" to discuss why this is the biggest problem with AI in 2026 - and why we're seeing so many failed rollouts. Pre-GPT, the problem was fragmentation. Post-GPT, the problem is…fragmentation. Frontier models are built on what Dheeraj calls a "world model" - they're made for general users, anywhere in the world. They come with an impressive understanding of the world. But… They don't know your customers. Or your entire support history. They don't know your products. Or the vital knowledge scattered across documents, timelines, contracts, email threads, Slack channels… That gap is why we built Computer: the only AI with native shared memory – which makes it the only AI that actually (really, honestly) knows how your business works Full interview: https://lnkd.in/gqvuVnnz Over to you: what's the biggest gap you're seeing between AI's promise – and what it's actually delivering? 👇