Resources
Blog
The Verification Gap: Why Autonomous Auditing Is Only as Good as What the AI Actually Read
Autonomous auditing is inevitable — and largely good if executed properly. But the question nobody is asking is what the AI is actually reading. Faster findings built on unverified documents aren't an audit improvement. They're audit risk at scale.
Autonomous Auditing Is Coming. The Knowledge Problem Is Already Here.
The Big Four estimate AI handles 20–30% of a typical financial audit by 2029. But the AI is only as trustworthy as the knowledge it's reading. Why verified knowledge architecture is the prerequisite for autonomous audit testing.
The Information Supply Chain Problem: Why Agentic Business Workflows Need More Than Efficient Retrieval
Even individually reasonable per-stage accuracy rates produce unacceptable end-to-end results when errors compound across agentic workflows. The solution requires a verified information supply chain that resets the error budget at each stage.
Anthropic's Study of 81,000 People Confirms What Enterprise AI Buyers Already Suspect: Unreliability Is the #1 Concern
Anthropic's landmark study of 81,000 people across 159 countries reveals unreliability as the top AI concern. Learn why RAG falls short and how verified knowledge architectures solve enterprise AI trust.
Technical Note: LAKEer on the FACTS Grounding Benchmark
Technical analysis of LAKEer's 77.7% score on the FACTS Grounding Benchmark — how it compares to frontier LLMs, the evaluation methodology, and the architectural principles that make it possible.
The Backstory on our FACTS Benchmark Results
Why we undertook the FACTS benchmark project, the engineering effort behind it, and what the industry-leading score of 77.7 means for enterprise AI customers who demand trustworthy, verifiable solutions.
The Denied Claim: Why Your AI Needs to Be a Detective, Not Just a Reader
How cross-document verification determines whether your IEEPA refund survives CBP scrutiny. A court denied an importer's refund claim not because documents were missing — but because there was no reliable way to connect them. Standard AI retrieves. LAKEer verifies.
Computational Knowledge and Reasoning — From Plato to Production Systems
A theoretical framework for computational knowledge grounded in three pillars: Provenance, Proof, and Context. Why justified knowledge is the antidote to AI slop in enterprise systems.
One Hallucinated Deadline Costs You the Refund. Here's the Architecture That Prevents It.
Standard RAG retrieves. LAKEer verifies. The difference shows up in your protest filings. See four high-stakes trade compliance questions compared side-by-side: standard LLM-RAG vs. LAKEer's 3D Graph verification architecture.
The SCOTUS Ruling Handed Importers a Legal Victory. It Also Created a Data Engineering Crisis.
Why recovering IEEPA tariff refunds is now an unstructured data problem — and why AI that hallucinates through it is a liability, not an asset. For mid-market importers, the 180-day protest window is a survival event.
$133 Billion in Tariff Refunds Are Up for Grabs. Here Is Exactly What It Takes to Collect Yours.
The Supreme Court ruled IEEPA tariffs unconstitutional. Between April 5, 2025 and that ruling, American importers paid an estimated $133 billion to $175 billion in duties that were never valid. The money is recoverable — but only if you file correctly under strict deadlines.
The SCOTUS Tariff Ruling Didn't End the Uncertainty. It Exposed Your Data Problem.
The Supreme Court struck down IEEPA tariffs, but the uncertainty isn't over — Plan B tariff mechanisms are already in motion. The enterprises that navigate this window will be the ones who can finally answer hard questions about their own contracts and supplier exposure data.
DaaX Business Model Innovation
Enterprise AI adoption is held back by outdated pricing models. Learn how DaaX's outcome-based, self-serve pricing with no long-term commitments removes friction and enables confident AI deployment.
Case Study: DaaX LAKEer vs. ChatGPT-5 – Oil & Gas Natural Language Search
We benchmarked DaaX LAKEer against ChatGPT-5 using a 100+ page oil well completion report. The results demonstrate that LAKEer consistently outperformed ChatGPT-5 in answer quality.
Preserving Critical Enterprise Knowledge: An AI-Powered Solution
The clock is ticking on one of the most significant challenges facing enterprises today: the imminent loss of critical institutional knowledge as experienced employees approach retirement. Learn how AI-powered solutions can help preserve decades of specialized expertise.
Discover how organizations in manufacturing, energy, and defense are addressing the knowledge exodus through systematic knowledge capture and AI-powered platforms.
Read full article →
DaaX Token Drop Podcast
A weekly, unscripted conversation from the DaaX team on the most interesting developments in AI. Sunil Baliga and Sajjad Khazipura (DaaX co-founders), along with Sam Pooni (DaaX Architect) and the occasional guest, explore, discuss, and debate new AI research, news, and real-world use cases. Built for developers and business leaders who want perspective from experienced AI practitioners.
| Episode | Description | Published | YouTube  | Spotify  | Apple Podcasts  |
|---|---|---|---|---|---|
| Episode 15 — The Invisible Layer: Why "Connective Tissue" — Not the Model — Is What Kills AI Projects at Scale | Six months after the demo wowed executives, the AI pilot quietly stalls — and the model is rarely to blame. Theo Forbath, founder of Above the Model and former Accenture MD, joins Token Drop to unpack the invisible \"connective tissue\" layer most companies underbuild: shared context, working and long-term memory, tool contracts, evaluation frameworks, and observability. | July 11, 2026 | Listen | ||
| Episode 14 — Algorithms Are Logarithmic, AI Is Quadratic — The Hidden Cost of Long Context Windows | This episode examines the quadratic scaling problem behind standard transformer attention. As the number of tokens grows, every token may need to interact with every other token—so doubling the context length can roughly quadruple the attention computation. | July 4, 2026 | Listen | ||
| Episode 13 — Who Decides What's "Safe" AI? Ethics, Trust & the Global Language Divide | Dr. Sarah Luger, AI safety and evaluation expert, joins Token Drop. We trace how the industry's language has shifted from ethics to responsible AI to trust and transparency to safety and security, and why that shift matters. | June 27, 2026 | Listen | ||
| Episode 12 — Your Employees Are Creating AI IP. Is Your Company Capturing It? | Werner Goertz, former Gartner analyst, Former AWS and IBM Analyst Relations leader, Founder of Anicca AR (Agent Relations) joins Token Drop to discuss a growing challenge in enterprise AI: employees are creating valuable prompts, workflows, and AI-assisted knowledge in individual accounts, but much of that value never becomes institutional knowledge. | June 20, 2026 | Listen | ||
| Episode 11 — How AI Is Changing Supply Chains | Supply chain executive Edwin de Boer joins Token Drop to break down where agentic AI genuinely moves the needle in supply chain — procurement negotiation, predictive maintenance, and shipment ETAs — and where the hype outpaces reality. The group digs into what actually builds trust in AI outputs, why data quality is the real bottleneck, the emerging distinction between "physical AI" and "knowledge AI," and building guardrails amid tariff volatility. | June 13, 2026 | Listen | ||
| Episode 10 — Why AI Agents Need an Operating System | The DaaX team argues that today's AI agents fall short not because LLMs need to get smarter, but because agentic systems are missing decades of distributed-systems thinking — fault tolerance, cache coherency, transactional boundaries, and persistent memory hierarchies. The group also unpacks three failure modes that quietly undermine multi-agent systems in production: memory poisoning, tail context, and cross-agent contradiction. | June 6, 2026 | Listen | ||
| Episode 9 — What Are Ontologies? Their Role in Knowledge Graphs and AI Domain Super Intelligence | The DaaX team digs into ontologies and knowledge graphs — and the term "domain superintelligence." The conversation traces how industry ontology standards (FIBO, OSDU) emerged, why LLMs plus tightly-scoped ontologies mitigate hallucinations far more reliably than pure LLM approaches, and why the economics of reusable domain cartridges make ontologies a pragmatic near-term path to real AI value. | May 30, 2026 | Listen | ||
| Episode 8 — Forward Deployed Engineers (FDEs) in AI - who, what, why, etc. | Special guest Satya Mantha, Principal Software Architect at Fission Labs, traces forward-deployed engineering from its Palantir origins to today's AI wave — why foundation-model benchmarks say little about enterprise behavior, why major AI labs are standing up their own consulting arms, and why context engineering never really finishes. | May 23, 2026 | Listen | ||
| Episode 7 — Wafer-Scale Computing After Cerebras: A Deep Dive on the Silicon Tradeoffs Behind AI Hardware | Prompted by Cerebras's recent IPO, special guest Raminda Madurawe — Founder & CEO of AxPro Semi and a veteran semiconductor architect — joins the DaaX team for a technical dive on wafer-scale silicon: the software, efficiency, and accuracy "tax" you always pay, why memory bandwidth (not compute) is the real bottleneck, and how Cerebras, SambaNova, and Groq compare architecturally. | May 16, 2026 | Listen | ||
| Episode 6 — Neuro-Symbolic AI Applied to the Networking Domain | This week the DaaX team discusses how neuro-symbolic AI, especially knowledge graphs, applies to the networking domain. | May 9, 2026 | Listen | ||
| Episode 5 — World Models, Explained: Are Knowledge Graphs Secretly the Same Idea? | The DaaX team unpacks world models — AI trained on video and sensor data rather than text — and asks whether knowledge graphs plus reasoning and probabilistic prediction are secretly the same idea, with concrete lessons from digital twins in supply chain and semiconductor manufacturing. | May 2, 2026 | Listen | ||
| Episode 4 — Open Source Catches Up: Why Open-Weight Models Are No Longer a Compromise | The DaaX team argues open-weight LLMs are no longer a compromise — GLM-5.1, Kimi K2, DeepSeek, and Qwen3 are matching or beating frontier models in a single month, DeepSeek at roughly one-seventh the token cost, turning model selection into a routing problem rather than a capability one. | April 25, 2026 | Listen | ||
| Episode 3 — Beyond A2A and MCP: Why Agent Governance Needs Its Own Layer | The DaaX team argues agent governance is the missing layer in enterprise AI — beyond A2A and MCP plumbing — with a three-layer policy pyramid, a quality-management parallel, and a concrete example of a "do not access production" rule quietly lost through context summarization. | April 18, 2026 | Listen | ||
| Episode 2 — Beyond RAG: Why Reasoning and Verification Are the Real Fix for LLM Hallucinations | Drawing on their semiconductor backgrounds, the DaaX team argues the 'humans make mistakes too' rationalization for LLM hallucinations breaks down. They cover why RAG alone isn't enough, pre- and post-synthesis verification, reasoning paired with reward models, and confidence calibration. | April 10, 2026 | Listen | ||
| Episode 1 — AI Hallucinations | This week the DaaX team discuss AI hallucinations. | April 4, 2026 | Listen | ||
Webinars
Upcoming
AI in Oil & Gas: Turning Complex Data into Actionable Intelligence
Explore how AI is transforming oil & gas by unlocking insights from complex, fragmented operational data. See real-world use cases that drive efficiency, safety, and better decision-making.
xOps for AI: Building and Operating Large-Scale Systems
Understand how xOps practices — DevOps, DataOps, and MLOps — enable teams to build and operate AI systems at scale. Learn how to improve reliability, reduce operational risk, and keep complex systems running smoothly in production.
Past
Introduction to Neuro-Symbolic AI
Discover how Neuro-Symbolic AI combines large language models with structured reasoning to build more reliable and explainable AI systems. Learn why enterprises are moving beyond LLM-only approaches to achieve trustworthy, production-ready results.
Scalable & Reliable Data Systems: The Foundation for Enterprise AI
Learn the core principles behind building data systems that can scale with growing demands while maintaining performance and reliability. This session covers practical architectures and best practices for supporting modern AI and data-driven applications.
Press
Official announcements from DaaX Technologies
DaaX Earns Awardable Status in the Department of War's Tradewinds Solutions Marketplace
DaaX has been assessed as "Awardable" by the Department of War's Chief Digital and Artificial Intelligence Office (CDAO) through the Tradewinds Solutions Marketplace. The designation makes DaaX's trustworthy AI solutions available for rapid acquisition across the DoW.
DaaX Launches Self-Service AI, Powered by Domain Knowledge Cartridges for Trustworthy Answers
DaaX today announced that LAKEer and SQLer are now available self-service. Customers can sign up at daax.ai and start using LAKEer and SQLer in minutes — beginning with a free plan, with no sales calls or procurement cycles.
DaaX to Host Four-Part Technical Webinar Series
DaaX announces a four-part technical webinar series featuring leading experts in neuro-symbolic AI, scalable data systems, xOps for AI, and real-world AI applications across industries. The series runs every three weeks starting June 2026 and is free to attend.
DaaX Achieves Industry-Leading Score of 77.7 on FACTS Benchmark
DaaX's LAKEer enterprise search agent achieved a FACTS grounding benchmark score of 77.7 on the FACTS Grounding Public Dataset — the best result published to date, surpassing the previous best of 74.3 by Gemini 2.5 Pro. The FACTS Benchmark Suite, introduced by Google DeepMind and Google Research, measures the factual accuracy of LLMs.
Interesting Stuff
Resources from DaaX and others that you may find interesting
From DaaX
7 Things 81,000 Enterprise Leaders Told Anthropic About AI
A visual breakdown of key findings from Anthropic's survey of 81,000 enterprise leaders on AI trust, reliability, and what to do about each concern.
Tariff Refund Resources
Free resources to help enterprises navigate the tariff refund recovery process after the Supreme Court's IEEPA ruling.
Tariff Refund Data Glossary — Key terms and definitions for customs data, timelines, and litigation-grade defensibility.
Tariff Refund Data Checklist — A structured checklist covering exposure discovery and litigation readiness data requirements.
Tools
DaaX has created a free custom AI tool that can be used by Marketing, Product Management, and Engineering to generate example customer natural language search queries.
To generate B-2-C example queries, please click here
To generate parametric search example queries, please click here
From others, including Academia
LLM Hallucinations
- Why Do Large Language Models Hallucinate?
- AA-Omniscience: Knowledge and Hallucination Benchmark
- Vectara's Hallucination Leaderboard
- Business Insider: "Snowflake CEO explains why 'the insidious thing' about AI hallucinations isn't the occasional error"
- Financial Times: "Deloitte issues refund for error-ridden Australian government report that used AI"