The New York-based startup says the platform places intelligent software assistants across daily operations, including sales, purchasing, inventory and finance. Its goal is to remove the manual work still used in food distribution.

Investors such as a16z Speedrun, Anterra Capital, Offline Ventures and Long Journey Ventures supported Anchr in the seed funding round. Executives from OpenAI also joined the investment.

Food distribution sits behind everyday commerce. Every restaurant order, supermarket shelf and catering delivery depends on it. However, much of the industry still runs on text messages, spreadsheets and ageing software.

Distributors handle hundreds of billions of dollars in perishable goods each year. Despite that scale, many teams still manage key processes manually.

Orders are typed into systems by hand, purchasing decisions rely on scattered spreadsheets and finance teams usually reconcile invoices across several disconnected platforms.

Anchr believes that gap creates an opportunity.

Most distributors rely on enterprise resource planning systems built to record past activity. Those systems log transactions but rarely guide future decisions. They do not forecast demand, optimise inventory in real time or warn teams about shrinking margins.

Other platforms focus mainly on digital ordering. For example, Choco and Pepper help customers place orders online. However, they stop there. Purchasing, reconciliation and margin analysis are still outside their scope.

As a result, many distributors use a patchwork of tools. Instead of simplifying operations, that mix often adds complexity.

Anchr’s platform sits on top of existing systems. Rather than replacing ERP software, it connects to it. The company says the software then handles tasks across order intake, purchasing, inventory planning, invoicing and collections.

Work that once required hours of manual input can now run automatically, with information carried across each step.

“The biggest opportunity to leverage AI isn’t in industries with modern infrastructure,” said Tzar Taraporvala, co-founder and Co-CEO of Anchr. “It’s buried deep in the operational backbone of the economy. Food distributors manage millions of dollars of inventory with systems that were never designed to handle today’s complexity.

“We built Anchr to become the intelligent layer that works alongside teams every single day, automating away the tedious, unsexy parts of the job to create truly material value for a margin-strapped business.”

The founders know the problem well, as Taraporvala and Smayan Mehra have built companies together for more than twenty years. Their interest in supply chain systems grew after seeing how disconnected many of them are.

A breakthrough came when they worked with a seafood distributor in Boston. The team spent months studying operations on the factory floor. What they found was unforgettable.

Staff entered orders into ERP systems at three in the morning, purchasing decisions came from fragmented spreadsheets and finance teams balanced invoices across several platforms.

For the founders, the inefficiencies were apparent and expensive.

Early users of the platform are already reporting measurable changes. One distributor recovered about 40% of daily working time across eight sales representatives. The profit came after automating order intake from text messages and emails.

Another company cut aged inventory losses by $30,000 in a single month. Better purchasing decisions, guided by live demand signals, helped achieve that.

Elsewhere, a customer expects to increase average basket size by roughly $65 per order. The system analyses menus and catalogues to suggest additional products.

In an industry where profit margins usually sit in low single digits, even small improvements can add up quickly.

The company’s early growth shows that urgency. Within 12 weeks of joining Speedrun, Anchr says it had already booked seven-figure revenue. Its customer base now ranges from regional distributors to a publicly traded company valued at about $5 billion.

“If the first era of enterprise software digitised record-keeping, we believe the next era will automate it. We call that shift Enterprise Resource Automation (ERA) – and Anchr is building this inevitable operating layer” said Smayan Mehra, co-founder and Co-CEO, Anchr.

With the seed funding, Anchr plans to expand automation across every layer of distributor operations. The aim is to create a system that supports every decision affecting product movement or financial flow.

Beyond food distribution, the founders see similar opportunities in other supply chains where physical goods move through fragmented systems.

“The magic here is compounding: when sales, purchasing, inventory, and finance share context, the whole business runs differently. Anchr is building an AI-native operating layer that turns fragmented steps into an integrated workflow and the early customer outcomes show what that unlocks,” said Troy Kirwin at a16z Speedrun.

The funding round was led by Radical Ventures, with participation from a16z Speedrun. New investors include Brendan O’Driscoll and Larry James Erwin.

To date, the company has raised $8.4 million with backers including Radical Ventures, a16z Speedrun and Comma Capital, alongside operators such as Aidan Gomez and executives from Braze.

General Magic builds automated agents for insurance firms. These agents answer routine questions, collect documents and follow up with customers. They operate across the insurance lifecycle, from pre-quote checks to post-quote engagement and claims coordination.

The company says its technology connects directly to broker management systems, quoting platforms and customer relationship systems already in use.

In early deployments with one of the world’s largest general insurers, General Magic reduced quote times from around 30 minutes to less than three. The reduction was achieved through an SMS-based agent that handles clarification and follow-ups automatically.

“Too much of insurance still relies on manual follow-through across calls, inboxes, and scattered systems,” said Jai Mansukhani, co-founder and president of General Magic.

“We focus on keeping customers engaged at every stage of the lifecycle, not just at quote or claim. Our agents handle the routine work that slows teams down, while giving insurance leaders real visibility into what customers are asking, where they are getting stuck, and how they are feeling.

“When that engagement and data flow directly into core systems, teams move faster and customers feel genuinely supported.”

At the centre of the company’s innovation is a product called Cell. It connects to broker systems, rating platforms and CRMs. Teams can deploy it through SMS, iMessage and RCS.

Customers can send questions by text, while the agent pulls data from internal systems, requests missing details and updates records as the process moves forward.

The company is currently working with insurers across motor and life lines, where follow-up after issuing a quote usually determines whether a sale is completed.

General Magic was founded by Anthony Azrak and Jai Mansukhani. Both previously built and sold technology products into established industries, then moved into insurance after dealing with repeated delays and high premiums following a water leak claim.

The founders say the industry works, but customer experience sometimes breaks down during important moments such as quoting and claims.

Retention is also a challenge across the insurance sector. Acquiring new customers costs more than keeping existing ones. With more policies being sold digitally and customers comparing prices at renewal, firms risk losing business after investing time and money to secure it.

Sanjana Basu, partner at Radical Ventures, said: “Most of the world’s financial and insurance data is locked inside rigid, legacy systems that were never designed for the AI era. General Magic isn’t trying to convince enterprises to throw away that infrastructure. Instead, they are giving them a way to finally talk to it. 

“By building a reasoning layer that sits on top of existing systems of record, the General Magic team are unlocking a massive amount of trapped value. 

“This is how the Fortune 500 becomes AI-native. Not by rebuilding from scratch, but by bridging the gap between old data and new intelligence.”

Troy Kirwin, investment partner at a16z Speedrun, added: “We’ve watched Anthony and Jai grow exponentially both during their speedrun cohort and in the months after. They are building a truly compelling product that we believe will revolutionise workflows across insurance carriers and brokerages globally. 

“I have a personal thesis that outsiders will disrupt legacy industries, and General Magic has helped buttress this thesis with the immense progress they’ve made. We are excited to deepen our partnership through supporting their seed round.”

Pete Tessier, BFA, CAIB, president at insurance MGA Taycon Risk, said: “What I have seen with General Magic and their approach to AI was a willingness to adapt to the insurance industry’s needs.

This is significant because of the varied nuances of the insurance industry and how its products are distributed and why internal and external customer journeys are different.

“The challenge will be making it scale across all channels of insurance product distribution. This might be the first true ‘game changer’ for the industry and deliver on customer experience and expectations”

General Magic plans to expand into more insurance lines and workflows with a focus on high-intent moments where communication gaps cost brokers and insurers time and revenue.

Teams want to launch campaigns, communicate with clients, and deploy AI-driven tools, yet every message must pass through manual review.

The result is weeks of delay, lost momentum, and teams avoiding written communication altogether. ZeroDrift was built to change that.

ZeroDrift recently announced its launch from stealth alongside a $2 million pre-seed round to automate compliance in real time, unlocking business velocity while giving compliance teams infrastructure to scale oversight.

The pre-seed round was led by a16z speedrun and brings ZeroDrift’s total funding to $2 million. The capital will support the company’s go-to-market launch, product expansion across communication channels, and continued development of its AI-driven compliance engine.

The timing reflects a growing tension across financial services and other regulated industries.

Firms are under pressure to move faster, scale digital outreach, and adopt AI, while regulatory requirements continue to demand strict oversight of every external communication.

Traditional compliance models rely on manual redlines, approval queues, and post-hoc sampling.

These processes were built for a different era and cannot scale with today’s communication volume, leaving compliance teams stretched thin and business teams waiting.

ZeroDrift takes a fundamentally different approach by shifting compliance from a gate at the end of the process into an automated guardrail that operates in real time.

ZeroDrift is an AI-native communication firewall that validates and fixes content before it is sent, giving compliance teams control at scale and business teams the speed to execute.

The platform encodes SEC, FINRA, and firm-specific policies into machine-readable rulepacks, then enforces them at the point of creation.

ZeroDrift integrates directly into tools teams already use, including email, browsers, CRMs, websites, social platforms, and AI systems.

Content is checked instantly, issues are flagged with suggested fixes, and compliant messages move forward without delay. Compliance teams retain full visibility through centralized dashboards, audit trails, and exam-ready evidence generated automatically.

“People do not want to be non-compliant. They just have no way to know if what they are writing is acceptable until it is too late,” said Kumesh Aroomoogan, founder and CEO of ZeroDrift. “Compliance should be a guardrail that lets teams move faster, not a gate that slows everything down. Our goal is to make compliance happen automatically at the speed of work.”

The idea for ZeroDrift came from founder Kumesh Aroomoogan’s experience building Accern (one of the first no-code AI platforms for financial services), which he exited by acquisition in 2025.

He repeatedly saw legal and compliance reviews stall launches and drain momentum.

He also noticed a more subtle shift, where people preferred phone calls over emails because they were unsure whether what they were writing was compliant. Compliance was not only slow, it was changing how people communicated.

ZeroDrift was created to solve that problem by giving teams certainty in real time.

ZeroDrift is launching initially in financial services, serving registered investment advisors, asset managers, broker-dealers, and wealth platforms.

The market includes more than 15,000 RIAs, 3,500 asset managers, and hundreds of thousands of registered representatives in the United States alone.

Early use cases include faster campaign launches, higher sales velocity, safe deployment of client-facing AI, and instant exam readiness without last-minute scrambles.

The broader shift toward AI and multi-channel communication is intensifying the problem ZeroDrift addresses. Firms now communicate across email, websites, social platforms, client portals, and AI assistants, each with its own compliance requirements.

Manual review does not scale across this landscape, and hiring more compliance staff is neither economical nor effective.

As communication volume increases, the firms that succeed will be those that automate governance rather than rely on human bottlenecks.

“Compliance has quietly become a limiting factor for how fast regulated companies can operate,” said Troy Kirwin from a16z speedrun. “ZeroDrift flips that dynamic by preventing violations before they happen and making compliance a built-in part of everyday workflows.”

Looking ahead, ZeroDrift plans to deepen its coverage across financial services before expanding its rule-based compliance engine into other regulated sectors, including insurance, healthcare, ESG disclosures, and AI governance.

The long-term vision is to become the universal trust layer for any system that communicates, ensuring that as AI and automation scale, trust, safety, and compliance scale with them.