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Zenzap raises $44M for its AI chat app that aims to replace WhatsApp in the workplace
AppWizard
October 15, 2026

Zenzap raises $44M for its AI chat app that aims to replace WhatsApp in the workplace

Businesses are increasingly using consumer-facing chat applications for staff communication and document sharing. Zenzap is a new private messaging platform led by Guy Weiss, designed for organizational context and compliance, featuring AI capabilities. The startup has secured funding from investors such as Bessemer, Lightspeed, and individual backers, marking Weiss's first fundraising effort after previously bootstrapping an e-commerce platform. Zenzap, founded in 2022, aims to serve various industries, offering features such as group chats, task management, calendar integration, and AI-powered tools on both free and paid plans. It currently counts clients like FedEx, Taco Bell, and Starbucks, and has a team of 50 employees across multiple locations. Zenzap's versatility is emphasized, as it targets a broader audience beyond developers, focusing on the majority of employees using personal messaging applications.
Windows 11 24H2 hits end of updates Oct. 13: What you should do now
Winsage
October 12, 2026

Windows 11 24H2 hits end of updates Oct. 13: What you should do now

Windows 11 version 24H2 for Home and Pro systems will stop receiving security updates on October 13, 2026. After this date, these editions will not receive any updates or technical support, although they will still boot. Windows 11 Enterprise, Education, IoT Enterprise, and Enterprise multi-session editions will continue to receive support until October 12, 2027. Organizations are advised to verify their systems' versions and editions, especially for those without endpoint management systems. Windows 11 25H2 and 26H2 are available as upgrade options, with 25H2 supported until October 12, 2027, and 26H2 supported until October 10, 2028, for Home and Pro editions. The rollout of 26H2 will be phased, and safeguard holds may be implemented if compatibility issues are detected. Unmanaged Home and Pro devices on 24H2 will automatically receive 25H2, while managed devices may require IT intervention. Regular monitoring and proactive management of Windows versions are necessary to ensure compliance and avoid future deadlines.
A practical guide to cost optimization with Lakebase Postgres
Tech Optimizer
October 11, 2026

A practical guide to cost optimization with Lakebase Postgres

Lakebase is a fully managed Postgres database designed for modern application development, featuring an architecture that separates storage and compute with a serverless compute layer. This design allows for cost efficiencies through various mechanisms: 1. **Branching**: Developers can create isolated environments for development, testing, or experimentation without duplicating storage costs, as branches share the same underlying storage. 2. **Autoscaling**: Lakebase adjusts compute resources based on activity levels, allowing users to pay only for the compute they use. It can scale down during low activity and can be suspended entirely after inactivity, reducing costs to zero. 3. **Read Replicas and High Availability**: The separation of storage and compute allows for adding read replicas and high availability without incurring additional storage costs, as these instances utilize the same storage layer. 4. **Synced Tables**: Integration with the Databricks Intelligence Platform enables efficient data syncing, allowing users to sync only the necessary working set of data, which helps avoid unnecessary storage and sync costs. 5. **Sync Modes**: There are three sync modes (Snapshot, Triggered, Continuous) for transferring data from the Lakehouse to Lakebase, each with different cost implications based on data freshness requirements. 6. **Right-sizing Compute**: Users can set the initial compute range during project provisioning to avoid over-provisioning and unnecessary costs. 7. **Monitoring and Metrics**: The Lakebase Metrics dashboard provides insights into working set size and cache utilization, helping users optimize their compute sizing and performance. 8. **Point-in-Time Restore (PITR) and Snapshots**: PITR maintains history for recovery within a configurable window, while snapshots offer discrete recovery points. Both are priced lower than standard storage, making them cost-effective options for data recovery. Lakebase costs are categorized into compute, storage, and serverless pipeline compute for syncing data. Compute is measured by CU usage, while storage includes branch storage, PITR history, and snapshot storage, all tracked separately. Users can access detailed usage and cost information through system billing tables.
AWS Embeds DuckDB in Aurora PostgreSQL, Enabling Direct Data Lake Queries Without ETL
Tech Optimizer
October 10, 2026

AWS Embeds DuckDB in Aurora PostgreSQL, Enabling Direct Data Lake Queries Without ETL

Amazon Web Services (AWS) has integrated the open-source analytics engine DuckDB into its Amazon Aurora PostgreSQL database, allowing users to query Apache Iceberg tables and Parquet files directly from data lakes without traditional ETL processes. This feature, announced on September 30, 2026, enables seamless access to both operational and historical data in a single SQL statement. Users can enable the aurora_analytics extension, assign an IAM role for S3 and AWS Glue access, and create external tables using standard PostgreSQL syntax. The integration supports Iceberg tables managed by AWS Glue Data Catalog, Iceberg REST Catalog-compatible external catalogs, Parquet files on S3, and S3 Tables. Performance optimizations include predicate pushdown and column pruning on the data lake side, with caching for frequently accessed data. This feature is available for Aurora PostgreSQL versions 17.11 and later, and 18.6 and later, across all commercial regions and AWS GovCloud (US), with no additional charges beyond Aurora compute and S3 request fees. In a separate development, AWS has a significant contract with AI company Anthropic, anticipating billion in cloud-related contractual obligations over several years, with approximately billion projected to be paid to Amazon from a 10-year agreement announced in April 2026. Anthropic's revenue has shown impressive growth, with first-quarter 2026 revenue reaching 0 million and second-quarter revenue at .8 billion. However, risks are present, as a significant portion of Anthropic's revenue comes from a few customers, and many larger clients lack long-term contracts. Amazon has invested .8 billion in Anthropic, with its stake valued at approximately billion as of June 2026.
Supabase Announces $150M in New Funding and Turso Acquisition
Tech Optimizer
October 10, 2026

Supabase Announces $150M in New Funding and Turso Acquisition

Supabase has secured 0 million in funding led by GIC, with participation from Alphabet's CapitalG, IronArc, and SquarePeg. This follows a million Series F round four months earlier. Supabase has acquired Turso, a platform for managing databases for agentic workloads, to enhance its product development and provide liquidity for employees. The company is adding over 1 million users and 4 million databases monthly, with 70% created by AI-driven tools, reflecting a 600% year-over-year increase in databases. Turso's architecture allows for on-demand provisioning of databases in public cloud and BYOC setups. Glauber Costa, founder of Turso, will become Head of Agentic Services at Supabase. Supabase, established in 2020, supports over 13 million developers with a comprehensive backend solution.
Why Antivirus Flags Game Tools and How to Verify Downloads Safely
Tech Optimizer
October 10, 2026

Why Antivirus Flags Game Tools and How to Verify Downloads Safely

In gaming, tools such as utilities, beta applications, and modding tools are often distributed as APK, IPA, or desktop files, and it is essential to investigate their origin, version, and any security warnings before installation. Antivirus software flags potential threats based on known malicious signatures, behavior patterns, and reputation data. Tools that modify game clients may receive heightened scrutiny, and classifications like “HackTool” or “Riskware” do not definitively indicate a file's functionality. Identical game utilities can exist on various platforms, and a familiar website does not guarantee authenticity. It is crucial to verify the publisher, update date, version, and installation method of a file. The SHA-256 hash verifies file integrity but does not ensure safety from malware. Calculating a file hash can be done using specific commands in Windows, macOS, or Linux. Multi-engine scanning platforms like VirusTotal provide insights, but a lack of detections does not guarantee safety. Even if a file matches its reference hash and raises no alerts, it may still violate online game terms. A pre-installation checklist includes confirming the publisher, checking file types, comparing SHA-256 hashes, reviewing security findings, keeping antivirus protection enabled, and consulting platform rules. A cautious approach integrates source verification, file integrity checks, security assessments, and compliance with platform regulations.
How and why we built Managed PostgreSQL for AI workloads
Tech Optimizer
October 10, 2026

How and why we built Managed PostgreSQL for AI workloads

The Nebius Managed PostgreSQL team developed a solution for AI workloads using CloudNativePG and Kubernetes, resulting in improved backup and restore times by transitioning from Barman to WAL-G, reducing a 1.5 TB backup duration from over a day to two hours. Since its launch in 2025, the service supports hundreds of production clusters and manages tens of tebibytes of data. Key features include high availability, point-in-time recovery, automated failover, compressed and encrypted backups, rapid restoration, connection pooling, and strict synchronous replication for zero data loss. Kubernetes and CloudNativePG were chosen for their advantages, including out-of-the-box features and open-source distribution. Each cloud project has a separate MK8s cluster for customer isolation and security. Persistent data is stored on fault-tolerant SSD drives, enabling swift instance migration during failures. Regular physical backups are archived, allowing restoration within a seven-day window with a single click. The transition from Barman to WAL-G addressed slow backup and restoration times and resource control limitations. With WAL-G, backups and restorations for a 1.5 TB cluster improved to two hours and one hour, respectively. PgBouncer was implemented to manage database connections effectively, reducing connection storms during peak AI workload traffic. Two vector search extensions, pgvector and pgvectorscale, are available to cater to different memory and dataset needs. Benchmarking showed that Nebius performs competitively with AWS at a lower cost. The infrastructure integrates cloud engineering principles with specialized expertise to meet AI workload demands.
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