Cutting cloud waste at scale: Akamai saves 70% using AI agents orchestrated by kubernetes
Akamai needed a Kubernetes automation platform that optimized the costs of running its core infrastructure in real time on several clouds.
venturebeat.com
Akamai needed a Kubernetes automation platform that optimized the costs of running its core infrastructure in real time on several clouds.
venturebeat.com
Observability startup Coralogix becomes a unicorn, eyes India expansion
Coralogix, an Israeli startup offering a full-stack observability and security platform, has raised $115 million at a pre-money valuation of over $1 billion, almost doubling in three years from its last round in 2022. With the influx of cash, the startup is looking to expand its engineering base in India and develop its AI agent. […]
techcrunch.com
Coralogix, an Israeli startup offering a full-stack observability and security platform, has raised $115 million at a pre-money valuation of over $1 billion, almost doubling in three years from its last round in 2022. With the influx of cash, the startup is looking to expand its engineering base in India and develop its AI agent. […]
techcrunch.com
DuckLake - Subsecond Latency on a Petabyte
DuckLake is one of the most exciting technologies in data.
While data lakes are powerful, the formats that manage them have become notoriously difficult to work with.
How does it achieve this? Instead of building a custom catalog server, DuckLake uses a simple, elegant idea: a standard database to manage metadata. It uses a database for what it’s good at. This clean architecture allows DuckLake to manage huge data lakes—with millions or even billions of files—across AWS S3 or Google Cloud Storage.
This simplicity also delivers incredible performance. In tests, DuckLake achieved sub-second query planning on a petabyte of data with 100 million snapshots—a scale that other systems can’t handle.
DuckLake speaks SQL, the lingua franca of data. Its architecture provides full ACID compliance, so concurrent reads and writes are handled seamlessly, allowing entire teams (and their AI agents) to work on the data lake simultaneously.
By returning to first principles, DuckLake delivers the power of a modern data lake without the complexity. Its simplicity and performance make it a vital part of the future of data.
www.tomtunguz.com
DuckLake is one of the most exciting technologies in data.
While data lakes are powerful, the formats that manage them have become notoriously difficult to work with.
“I think one of the things in DuckLake that we managed to do is to cut, I want to say like 15 technologies out of this stack.”
How does it achieve this? Instead of building a custom catalog server, DuckLake uses a simple, elegant idea: a standard database to manage metadata. It uses a database for what it’s good at. This clean architecture allows DuckLake to manage huge data lakes—with millions or even billions of files—across AWS S3 or Google Cloud Storage.
This simplicity also delivers incredible performance. In tests, DuckLake achieved sub-second query planning on a petabyte of data with 100 million snapshots—a scale that other systems can’t handle.
DuckLake speaks SQL, the lingua franca of data. Its architecture provides full ACID compliance, so concurrent reads and writes are handled seamlessly, allowing entire teams (and their AI agents) to work on the data lake simultaneously.
By returning to first principles, DuckLake delivers the power of a modern data lake without the complexity. Its simplicity and performance make it a vital part of the future of data.
www.tomtunguz.com
DuckLake - Subsecond Latency on a Petabyte
DuckLake is one of the most exciting technologies in data.
While data lakes are powerful, the formats that manage them have become notoriously difficult to work with.
How does it achieve this? Instead of building a custom catalog server, DuckLake uses a simple, elegant idea: a standard database to manage metadata. It uses a database for what it’s good at. This clean architecture allows DuckLake to manage huge data lakes—with millions or even billions of files—across AWS S3 or Google Cloud Storage.
This simplicity also delivers incredible performance. In tests, DuckLake achieved sub-second query planning on a petabyte of data with 100 million snapshots—a scale that other systems can’t handle.
DuckLake speaks SQL, the lingua franca of data. Its architecture provides full ACID compliance, so concurrent reads and writes are handled seamlessly, allowing entire teams (and their AI agents) to work on the data lake simultaneously.
By returning to first principles, DuckLake delivers the power of a modern data lake without the complexity. Its simplicity and performance make it a vital part of the future of data.
www.tomtunguz.com
DuckLake is one of the most exciting technologies in data.
While data lakes are powerful, the formats that manage them have become notoriously difficult to work with.
“I think one of the things in DuckLake that we managed to do is to cut, I want to say like 15 technologies out of this stack.”
How does it achieve this? Instead of building a custom catalog server, DuckLake uses a simple, elegant idea: a standard database to manage metadata. It uses a database for what it’s good at. This clean architecture allows DuckLake to manage huge data lakes—with millions or even billions of files—across AWS S3 or Google Cloud Storage.
This simplicity also delivers incredible performance. In tests, DuckLake achieved sub-second query planning on a petabyte of data with 100 million snapshots—a scale that other systems can’t handle.
DuckLake speaks SQL, the lingua franca of data. Its architecture provides full ACID compliance, so concurrent reads and writes are handled seamlessly, allowing entire teams (and their AI agents) to work on the data lake simultaneously.
By returning to first principles, DuckLake delivers the power of a modern data lake without the complexity. Its simplicity and performance make it a vital part of the future of data.
www.tomtunguz.com
OpenAI open sourced a new Customer Service Agent framework — learn more about its growing enterprise strategy
By offering transparent tooling and clear implementation examples, OpenAI is pushing agentic systems out of the lab and into everyday use.
venturebeat.com
By offering transparent tooling and clear implementation examples, OpenAI is pushing agentic systems out of the lab and into everyday use.
venturebeat.com
AI optimism in APAC security rises, but data readiness lags behind: Report
As artificial intelligence (AI) becomes both a defensive tool and a target in the cybersecurity arms race, new research from Salesforce reveals a mixed picture among Asia Pacific (APAC) security leaders. While there is near-universal optimism about AI agents’ potential to enhance cybersecurity, a sobering half of surveyed IT leaders acknowledge their organisations are not […]
The post AI optimism in APAC security rises, but data readiness lags behind: Report appeared first on e27.
e27.co
As artificial intelligence (AI) becomes both a defensive tool and a target in the cybersecurity arms race, new research from Salesforce reveals a mixed picture among Asia Pacific (APAC) security leaders. While there is near-universal optimism about AI agents’ potential to enhance cybersecurity, a sobering half of surveyed IT leaders acknowledge their organisations are not […]
The post AI optimism in APAC security rises, but data readiness lags behind: Report appeared first on e27.
e27.co
Belgium’s Bizzy raises €4M to help sales teams stop chasing leads and start closing deals
Ghent-based Bizzy has secured €4M in funding to expand its AI Sales Agent across Europe. Fortino Capital led the round. Fortino leads growth-stage investments across European SaaS companies, with particular expertise in sales automation and data intelligence platforms. The round also saw participation from prominent Belgian investors, including founders of Silverfin, Lighthouse, Teamleader, and Henchman ... Read more
siliconcanals.com
Ghent-based Bizzy has secured €4M in funding to expand its AI Sales Agent across Europe. Fortino Capital led the round. Fortino leads growth-stage investments across European SaaS companies, with particular expertise in sales automation and data intelligence platforms. The round also saw participation from prominent Belgian investors, including founders of Silverfin, Lighthouse, Teamleader, and Henchman ... Read more
siliconcanals.com
Silicon Florist links arrangement for June 20, 2025
Here’s a roundup of interesting startup links I came across today: Why We Invested: Conveyor — Oregon Venture Fund We’re particularly excited about their roadmap and believe Conveyor is poised to lead the evolution toward truly agentic, AI-driven B2B buying and selling workflows. The company is architecting a future where a buyer’s AI agent can ...
siliconflorist.com
Here’s a roundup of interesting startup links I came across today: Why We Invested: Conveyor — Oregon Venture Fund We’re particularly excited about their roadmap and believe Conveyor is poised to lead the evolution toward truly agentic, AI-driven B2B buying and selling workflows. The company is architecting a future where a buyer’s AI agent can ...
siliconflorist.com
Botpress secures $25M to scale AI agent infrastructure
Investment to Drive Development of Cloud Platform, Expansion of Global Services
The post Botpress secures $25M to scale AI agent infrastructure appeared first on StartUp Beat.
startupbeat.com
Investment to Drive Development of Cloud Platform, Expansion of Global Services
The post Botpress secures $25M to scale AI agent infrastructure appeared first on StartUp Beat.
startupbeat.com
Why we’re focusing VB Transform on the agentic revolution – and what’s at stake for enterprise AI leaders
VB Transform 2025 tackles the agentic AI revolution—how enterprises can close the infrastructure gap and turn dazzling demos into deployed, trusted agents.
venturebeat.com
VB Transform 2025 tackles the agentic AI revolution—how enterprises can close the infrastructure gap and turn dazzling demos into deployed, trusted agents.
venturebeat.com
Salesforce launches Agentforce 3 with AI agent observability and MCP support
Salesforce launches Agentforce 3 with AI agent observability and native MCP support, giving enterprises real-time visibility and secure interoperability at scale.
venturebeat.com
Salesforce launches Agentforce 3 with AI agent observability and native MCP support, giving enterprises real-time visibility and secure interoperability at scale.
venturebeat.com
Could I Really Automate 80% of My Business With AI? I Decided to Find Out
How I used AI agents to escape busywork, reclaim time and grow my solo businessContinue reading on The Startup »
medium.com
How I used AI agents to escape busywork, reclaim time and grow my solo businessContinue reading on The Startup »
medium.com
Emergence AI’s CRAFT arrives to make it easy for enterprises to automate their entire data pipeline
EXCLUSIVE: New York City based startup Emergence AI, founded by former IBM researchers, previously made headlines for its impressive automated system that allows enterprises to type in a requested task in plain natural language and automatically create a fleet of agents to help complete it. But that’s not all the company has up its sleeve when […]
venturebeat.com
EXCLUSIVE: New York City based startup Emergence AI, founded by former IBM researchers, previously made headlines for its impressive automated system that allows enterprises to type in a requested task in plain natural language and automatically create a fleet of agents to help complete it. But that’s not all the company has up its sleeve when […]
venturebeat.com
How CISOs became the gatekeepers of $309B AI infrastructure spending
Security vendors race to control $309B AI infrastructure market. How AgenticOps, eBPF and silicon-speed security will determine the winners.
venturebeat.com
Security vendors race to control $309B AI infrastructure market. How AgenticOps, eBPF and silicon-speed security will determine the winners.
venturebeat.com
Pipes.ai: Supercharge Sales With AI-Powered Lead Conversion
Managing lead volume is one of the most frustrating challenges for sales organizations. Too often, marketing teams capture web leads that never convert because sales teams can’t follow up quickly enough or waste time chasing bad data. The result? Bloated pipelines, missed revenue, and high agent burnout. There’s a better way to turn intent into …
feed.martech.zone
Managing lead volume is one of the most frustrating challenges for sales organizations. Too often, marketing teams capture web leads that never convert because sales teams can’t follow up quickly enough or waste time chasing bad data. The result? Bloated pipelines, missed revenue, and high agent burnout. There’s a better way to turn intent into …
feed.martech.zone
What’s inside Genspark? A new vibe working approach that ditches rigid workflows for autonomous agents
Genspark's autonomous AI agents prove that less control beats rigid workflows, forcing enterprise AI leaders to rethink how they architect intelligent systems.
venturebeat.com
Genspark's autonomous AI agents prove that less control beats rigid workflows, forcing enterprise AI leaders to rethink how they architect intelligent systems.
venturebeat.com
Enterprises must rethink IAM as AI agents outnumber humans 10 to 1
Identity is the essential control plane for agentic AI security, redefining enterprise defenses amid rising credential-based breaches.
venturebeat.com
Identity is the essential control plane for agentic AI security, redefining enterprise defenses amid rising credential-based breaches.
venturebeat.com
Rubrik acquires Predibase to accelerate adoption of AI agents
Predibase helps companies train and fine-tune open source AI models which will help Rubrik customers deploy AI agents faster.
techcrunch.com
Predibase helps companies train and fine-tune open source AI models which will help Rubrik customers deploy AI agents faster.
techcrunch.com
Why Data is More Valuable than Code
In “Data Rules Everything Around Me,” Matt Slotnick wrote about the difference between SaaS & AI apps.
A typical SaaS app has a workflow layer, a middleware/connectivity layer, & a data layer/database. So does an AI app.
AI makes writing frontends trivial, so in the three-layer cake of workflow software the data matters much more.
The big differences between an AI & the SaaS app lie within the ganache of the middle layer. In SaaS applications, coded business rules determine each step a lead follows from creation to close.
In AI apps, a non-deterministic AI model decides the steps using context : relevant information about the lead that the AI is querying from other sources.
The better the data, the better the workflow.
The context is the most valuable component because it ultimately changes the workflow. Models are relatively similar in performance.
For example, an inbound email comes into a customer support desk, “Was I double charged this month?” An agentic workflow would query the billing system, the contract system, & the email drafting tool to draft an email to the customer with distinct language for that persona. This only works if the enterprises’ data is well structured.
Enterprises will be shy about sharing the context with their vendors because of how much value it provides. They may start to structure it & assign a department to manage it because the better its availability, the more effective the agentic systems will be.
Data architecture may become a competitive advantage & the future battleground for software companies will be the access to that context - & the fight has already begun.
www.tomtunguz.com
In “Data Rules Everything Around Me,” Matt Slotnick wrote about the difference between SaaS & AI apps.
A typical SaaS app has a workflow layer, a middleware/connectivity layer, & a data layer/database. So does an AI app.
AI makes writing frontends trivial, so in the three-layer cake of workflow software the data matters much more.
The big differences between an AI & the SaaS app lie within the ganache of the middle layer. In SaaS applications, coded business rules determine each step a lead follows from creation to close.
In AI apps, a non-deterministic AI model decides the steps using context : relevant information about the lead that the AI is querying from other sources.
The better the data, the better the workflow.
The context is the most valuable component because it ultimately changes the workflow. Models are relatively similar in performance.
For example, an inbound email comes into a customer support desk, “Was I double charged this month?” An agentic workflow would query the billing system, the contract system, & the email drafting tool to draft an email to the customer with distinct language for that persona. This only works if the enterprises’ data is well structured.
Enterprises will be shy about sharing the context with their vendors because of how much value it provides. They may start to structure it & assign a department to manage it because the better its availability, the more effective the agentic systems will be.
Data architecture may become a competitive advantage & the future battleground for software companies will be the access to that context - & the fight has already begun.
www.tomtunguz.com
Why Data is More Valuable than Code
In “Data Rules Everything Around Me,” Matt Slotnick wrote about the difference between SaaS & AI apps.
A typical SaaS app has a workflow layer, a middleware/connectivity layer, & a data layer/database. So does an AI app.
AI makes writing frontends trivial, so in the three-layer cake of workflow software the data matters much more.
The big differences between an AI & the SaaS app lie within the ganache of the middle layer. In SaaS applications, coded business rules determine each step a lead follows from creation to close.
In AI apps, a non-deterministic AI model decides the steps using context : relevant information about the lead that the AI is querying from other sources.
The better the data, the better the workflow.
The context is the most valuable component because it ultimately changes the workflow. Models are relatively similar in performance.
For example, an inbound email comes into a customer support desk, “Was I double charged this month?” An agentic workflow would query the billing system, the contract system, & the email drafting tool to draft an email to the customer with distinct language for that persona. This only works if the enterprises’ data is well structured.
Enterprises will be shy about sharing the context with their vendors because of how much value it provides. They may start to structure it & assign a department to manage it because the better its availability, the more effective the agentic systems will be.
Data architecture may become a competitive advantage & the future battleground for software companies will be the access to that context - & the fight has already begun.
www.tomtunguz.com
In “Data Rules Everything Around Me,” Matt Slotnick wrote about the difference between SaaS & AI apps.
A typical SaaS app has a workflow layer, a middleware/connectivity layer, & a data layer/database. So does an AI app.
AI makes writing frontends trivial, so in the three-layer cake of workflow software the data matters much more.
The big differences between an AI & the SaaS app lie within the ganache of the middle layer. In SaaS applications, coded business rules determine each step a lead follows from creation to close.
In AI apps, a non-deterministic AI model decides the steps using context : relevant information about the lead that the AI is querying from other sources.
The better the data, the better the workflow.
The context is the most valuable component because it ultimately changes the workflow. Models are relatively similar in performance.
For example, an inbound email comes into a customer support desk, “Was I double charged this month?” An agentic workflow would query the billing system, the contract system, & the email drafting tool to draft an email to the customer with distinct language for that persona. This only works if the enterprises’ data is well structured.
Enterprises will be shy about sharing the context with their vendors because of how much value it provides. They may start to structure it & assign a department to manage it because the better its availability, the more effective the agentic systems will be.
Data architecture may become a competitive advantage & the future battleground for software companies will be the access to that context - & the fight has already begun.
www.tomtunguz.com
Creatio’s new 8.3 Twin CRM update hits Salesforce where it hurts: ‘we don’t think of AI as an add-on…it’s just part of our app experience’
Customers can control which documents are persistent for agent grounding and manage access to ensure regulatory compliance.
venturebeat.com
Customers can control which documents are persistent for agent grounding and manage access to ensure regulatory compliance.
venturebeat.com