🚀 We’re out of stealth - and announcing our $9M seed round led by @FoundationCap. Finance runs on trust. But today, that trust is fragile - held together by late nights in spreadsheets and manual reconciliations. Maximor makes that trust unbreakable. We’re honored to have this milestone covered by Forbes, TechCrunch, Axios, Wall Street Journal & others! Full story in the thread 🧵👇 #AI #Finance #Startups

hard AGREE - this is the future of enterprise! And that brings with it the need to then re-invent how ROI of decisions across both human & token capital are measured. The CFO will play a key role in defining the loss function of this company-wide self-learning AI layer. Corporate finance will need to be completely re-invented though. We are doing it! @maximor_ai PS. Kudos to @JayaGup10 for calling this early with her context graph series 🤝

RT @ajkrish95: Great read!! CFOs are increasingly becoming the single most important person in enterprises. And @maximor_ai being the Clea…

Uff.. another banger! Here's another macro shift happening: If intelligence is a priced resource, then the CFO becomes the most important person at the company – the one allocating spend & analyzing ROI across the only 4 inputs that matter: customers, employees, vendors, and now.. tokens. That allocation problem is unsolved. We've already figured it out for all of finance. For 20 years IT/engineering decided what companies bought. AI hands that power to the CFO. It's the CFO's turn to take it. We're arming them. @maximor_ai 🫡

Day 1 at Gartner Finance Symposium cooked!🔥One question kept coming up: "We've got people building agents in Claude, Vertex, Codex – how do we govern all of this?" The worry is real. Finance teams are vibecoding fast with DIY agents, but nobody has an answer for what happens when you have hundreds running with no audit trail, no policy layer, and no way to know if they're still doing the right thing when your processes change next quarter. And even if you get an agent working today, it's trained on a snapshot of right now. Transaction patterns shift. Policies update. New subs come in. If the agent can't learn and adapt with you, you're just building technical debt with better branding. This is what we built @maximor_ai to solve – agents that don't just automate a frozen process, but continuously learn from your team's judgment and evolve as your business does. One policy layer. Full audit trail. Human in the loop for the exceptions. Best part of today – these weren't 2-minute booth drive-bys. CFOs and controllers pulling up chairs, going deep on AI strategy, and at one point I'm explaining how context graphs differ from knowledge graphs. At a finance conference. Who would have expected!! (h/t @JayaGup10 🫡) If you're at the Gartner Xpo tomorrow, come find us at Booth 109!

Huge congrats to @ramkris from Maximor on two stellar CFO conferences this week. Very few people are so technically deep in AI and context engineering along with prior exposure to the messy world of enterprise transformations. 🚀🚀🚀

#31: #AIRadarDaily — @maximor_ai Companies pour millions into enterprise ERP systems, expecting a complete digital transformation. Yet, at the end of every month, finance teams are still trapped in a mess of manual processes. They spend nights and weekends pulling data from fragmented systems, reconciling accounts, parsing contracts, and fighting fires in massive spreadsheets. ERP migrations promised to fix this, but they usually just move the bottleneck. Finance leaders don't want another disruptive software migration; they want the busywork to disappear. Maximor AI is building the always-on finance team to handle the grind. Founded by Ramnandan Krishnamurthy and Ajay Krishna Amudan, Maximor is an AI-native finance automation platform built for the strategic CFO. The brilliance of Maximor is that it doesn't force companies to rip and replace their existing tech stack. Instead, their proprietary "Audit-Ready Agents" plug directly into the tools a company already uses — ERPs, CRMs, payroll, and banking systems. These specialized AI agents act as a tireless back-office team. They handle the heavy lifting: reconciling global cash positions, preparing journal entries, allocating revenue across complex contracts, and running flux analysis. Crucially, they don't just output raw numbers; they generate fully traceable, audit-ready evidence by default. The human finance team simply reviews the exceptions. The market? Any mid-market or enterprise company struggling with the realities of the accounting industry: a shrinking CPA pipeline, exploding financial complexity, and multi-entity operations. Ramnandan and Ajay spent years leading global digital transformation projects at Microsoft. They saw firsthand how critical workflows were constantly forced back into manual spreadsheets despite massive IT budgets. They realized that finance doesn't need another generic SaaS tool; it needs an intelligent action layer that does the work for you. They are building the infrastructure that lets finance leaders stop firefighting and start actually guiding the business. Let's celebrate the builders. w/ Jay Ingle & Dikshant Joshi #FinanceAutomation #AIBoomiAnnual26

Strong argument for who can build the strongest context graphs: execution agents >> search copilots Former is the net new opportunity if you can capture decision traces in the write path Latter is what incumbents are layering on top of existing systems of records in the read path

@weareplayerzero, @maximor_ai, and @tryolivai are great examples of this. PlayerZero builds the context graph by automating L2/L3 support - sitting at the intersection where code, config, infrastructure, and customer behavior collide. Maximor captures decision lineage by orchestrating finance workflows where reconciliation logic and exceptions actually live. Oliv builds it for sales - starting as a co-pilot that performs specific tasks (update CRM, send follow-up) and capturing the decision traces along the way.

Adding a finance / accounting lens here (@maximor_ai building enterprise finance automation without ERP brain surgery). Judgment in these teams lives in very specific places. Controllers face concrete problems: recons that didn’t tie, accruals that are late, RevRec edge cases, audit questions, or a close that’s drifting. Progress tends to come from handling those exceptions well. Clear policy checks with evidence attached. Someone accountable for the call. Something an auditor can follow later. When that works, context builds on its own in a structured, deterministic way. You can see why an entry was changed, who approved it, what changed from last time, and what precedent applies. The decision layer matters. In finance, it shows up after execution earns trust.

NOT an armchair 2026 predictions post If you’re in corporate finance, you should check this out PS. We have a wager internally on how this pans out

Maximor = system of record for decisions in finance & accounting

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High leverage opportunity - join us!

Thanks for featuring us @JayaGup10 ! 🔥

We def need Cursor for monthly board decks & financials Good thing we're building that at Maximor

Come join us!!

I do think department-specific agents will emerge. For Finance & Accounting, we’re building Maximor to be the leader.

Automating the drudgery of financial accounting has always been obvious in value. Every company needs it. Several have tried and “failed” with a tech facade masquerading humans in Philippines/India doing the work. It’s different now. With Maximor.