by Gary Mintchell | Jul 7, 2025 | Data Management
This news concerns unstructured data management. I wrote about Datadobi several times in 2021 and 2022. Not much since. They have released a new version of their StorageMAP, its “heterogeneous unstructured data management solution.”
StorageMAP 7.3 enables organizations to create policy-driven workflows, act on data more precisely, and migrate between S3-compatible platforms while maintaining compliance.
StorageMAP 7.3 introduces policy-driven workflows that allow administrators to define tasks executed by its workflow engine in response to specific triggers, such as a time schedule. A “dry run” feature facilitates reviewing the scope of a policy before full execution.
These new workflows support a wide range of use cases, including periodic automated archival, creating data pipelines to feed GenAI applications, identifying and relocating non-business-related data to a quarantine area, and more. Once policies are published, StorageMAP runs the workflows on schedule without requiring manual supervision.
In addition, StorageMAP 7.3 adds support for granular file-level deletes. Administrators can identify files that match specific criteria and save them as input to a targeted delete job, which StorageMAP will execute. Each delete job generates a report that documents the job’s details and outcome.
This functionality addresses situations where a coarse-grained directory-level deletion is not possible due to the presence of both relevant and disposable data. By enabling precise file selection, StorageMAP ensures that administrators can apply accurate and effective deletion policies.
Object migration enhancements
StorageMAP 7.3 also enhances its core object migration functionality by supporting the migration of locked objects between S3-compatible storage systems. This allows compliant data stored in a Write Once Read Many (WORM) format to be relocated across different vendor platforms while retaining its retention date and legal holds.
To support cost and performance objectives, the solution includes the ability to select the S3 storage class during object migration or replication. By specifying the desired storage class at the time of the job, organizations can avoid unnecessary post-migration lifecycle policies and ensure data is written directly to the appropriate tier.
by Gary Mintchell | Jul 4, 2025 | Personal Development
Every year I suggest that all Americans take some time to read a few things to refresh our memories about the founding of our country. It’s probably not a bad practice for all of you who do not live here just for the ideals.
Read
- The Declaration of Independence
- The Preamble to the Constitution
- Actually the entire Constitution
- If not all, at least the first 10 amendments—the Bill of Rights
- Bonus points—read The Federalist Papers
These documents are full of compromises—something that has made it last so long. And something we seem unwilling to do this past decade or so.
by Gary Mintchell | Jul 3, 2025 | News
PwC have released a report on industrial manufacturing merger & acquisition (M&A) activity for the first half of 2025. The report suggests a recalibration of capital allocation in response to shifting macro conditions.
Deal volume moderated amid new US tariffs, geopolitical volatility and selective private equity (PE) engagement. Yet, investors are pursuing high-conviction opportunities aligned with long-term structural trends. Strategic buyers and sponsors are doubling down on automation, defense and energy transition — sectors where innovation, policy support and resilience to cyclicality are driving premium valuations and sustained interest.
Key developments include:
- Tariff-induced valuation gaps: Newly implemented US tariffs introduced friction into cross-border dealmaking, stalling transactions with international exposure and widening bid-ask spreads.
- Strategic divestitures accelerate: Corporations are intensifying portfolio optimization efforts, shedding non-core assets to refocus on high-growth areas. Notably, several industrial conglomerates announced spin-offs in the advanced materials segment.
- Tech-driven acquisitions: Demand for automation, AI and digital transformation capabilities continues to drive acquisitions aimed at enhancing productivity and operational agility.
- Supply chain reconfiguration: Heightened geopolitical and trade risks are prompting companies to reevaluate supply chain dependencies. This is fueling interest in domestic and nearshore M&A as part of broader resilience strategies.
- PE’s selective deployment: While overall PE activity slowed, firms remain active in resilient sectors — particularly technology and business services — where tariff exposure is limited and long-term value creation remains viable.
Looking ahead: Navigating uncertainty with strategic focus
Key strategic considerations include:
- Staying ahead of policy shifts: Ongoing trade negotiations and potential regulatory changes could materially affect cross-border deal flows. Proactive monitoring and scenario planning will be essential to maintain deal momentum.
- Reinforcing due diligence discipline: In a complex geopolitical and economic environment, thorough due diligence remains critical to assess risk, validate value creation potential and enable strategic alignment.
- Harnessing technology for competitive advantage: Automation, AI and digital tools are increasingly central to industrial competitiveness. M&A and internal investment targeting these capabilities should be a strategic priority.
- Targeting high-growth, policy-backed sectors: Government-backed initiatives in defense and infrastructure continue to support robust deal pipelines. Strategic acquirers should explore opportunities where public funding and private innovation intersect.
- Reshaping supply chains through M&A: As companies adapt to geopolitical risks and cost pressures, acquisitions of nearshore or domestic suppliers can enhance supply chain resilience and agility.
by Gary Mintchell | Jul 2, 2025 | Personal Development
Learning is not compulsory…neither is survival—W. Edwards Deming, quality master
There are people who have a set of things they know and judge all events and actions against that set. There are people who have the continuous unease of not knowing. The former can be typed (perhaps too rigidly) as “FJ or Feeling Judgmental” on the Myers-Briggs Types Indicator. The latter as “TP or Thinking Perceptive.” Anyone who has read more than a few of my thoughts can easily figure out which type describes me.
At that time the disciples came to Jesus and asked, “Who, then, is the greatest in the kingdom of heaven?” He called a little child to him, and placed the child among them. And he said: “Truly I tell you, unless you change and become like little children, you will never enter the kingdom of heaven. Therefore, whoever takes the lowly position of this child is the greatest in the kingdom of heaven. And whoever welcomes one such child in my name welcomes me.—Matthew 18
As with all spiritual texts, this can be open to numerous interpretations. I choose in this context to reflect on “beginner’s mind.” Wisdom about as ancient as humans in community recognizes that if our heads are full of knowledge or “stuff,” then there is no room for growth, for learning.
Unless we change and become as little children, that is, unless we are open and fascinated to learn more, we will be stuck where we are.
Seth Godin remarked, “Learning is the difficult work of experiencing incompetence on our way to mastery.”
Unless we become like children—stumbling until we suddenly walk; needing an adult to keep the bicycle up until suddenly we are riding; stumbling over pronouncing a new word until suddenly we are fluent.
Where do you feel the tension of unease of not knowing that will entice you into trying until you learn?
by Gary Mintchell | Jul 1, 2025 | Generative AI
Deepgram is an intriguing company. Have they solved the problem that Apple still misses with Siri or Amazon with its new Alexa? They bill themselves as “World’s Only Enterprise-Ready, Real-Time, and Cost-Effective Conversational AI API.” They have developed a voice AI platform.
In addition, its CEO Scott Stephenson has become a YouTuber with a YouTube channel (billed as a podcast, but it isn’t one), “The Scott Stephenson AI Show” — A No-Hype, Deep-Dive Podcast on the AI Revolution. Oh, he’s also on Spotify. I am not. I download podcasts on Overcast. I haven’t the time to watch many 40+ minute YouTube videos. I’ve watched much of this one. He does provide a knowledgeable overview in this episode.
Back to the Deepgram API.
Deepgram announced the general availability (GA) of its Voice Agent API, a single, unified voice-to-voice interface that gives developers full control to build context-aware voice agents that power natural, responsive conversations. Combining speech-to-text, text-to-speech, and large language model (LLM) orchestration with contextualized conversational logic into a unified architecture, the Voice Agent API gives developers the choice of using Deepgram’s fully integrated stack (leveraging industry-leading Nova-3 STT and Aura-2 TTS models) or bringing their own LLM and TTS models. It delivers the simplicity developers love and the controllability enterprises need to deploy real-time, intelligent voice agents at scale. Today, companies like Aircall, Jack in the Box, StreamIt, and OpenPhone are building voice agents with Deepgram to save costs, reduce wait times, and increase customer loyalty.
I can no longer download and play with software like in the old days. I’d suggest that if you’re a developer and need a voice assistant, try it out.
For teams taking the DIY route, the challenge isn’t just connecting models but also building and operating the entire runtime layer that makes real-time conversations work. Teams must manage live audio streaming, accurately detect when a user has finished speaking, coordinate model responses, handle mid-sentence interruptions, and maintain a natural conversational cadence. While some platforms offer partial orchestration features, most APIs do not provide a fully integrated runtime. As a result, developers are often left to manage streaming, session state, and coordination logic across fragmented services, which adds complexity and delays time to production.
Deepgram’s Voice Agent API removes this burden by providing a single, unified API that integrates speech-to-text, LLM reasoning, and text-to-speech with built-in support for real-time conversational dynamics. Capabilities such as barge-in handling and turn-taking prediction are model-driven and managed natively within the platform. This eliminates the need to stitch together multiple vendors or maintain custom orchestration, enabling faster prototyping, reduced complexity, and more time focused on building high-quality experiences.
In addition to the Voice Agent API, organizations seeking broader integrations can leverage Deepgram’s extensive partner ecosystem, including Kore.ai, OneReach.ai, Twilio and others, to access comprehensive conversational AI solutions and services powered by Deepgram APIs.
Key capabilities include:
- Flexible Deployment: Run the complete voice stack in cloud, VPC, or on-prem environments to meet enterprise requirements for security, compliance, and performance.
- Runtime-Level Orchestration: Deepgram’s runtime supports mid-session control, real-time prompt updates, model switching, and event-driven signaling to adapt agent behavior dynamically.
- Bring-Your-Own Models: Teams can integrate their own LLMs or TTS systems while retaining Deepgram’s orchestration, streaming pipeline, and real-time responsiveness.
In addition to control and performance, the Voice Agent API is built for cost efficiency across large-scale deployments. When teams run entirely on Deepgram’s vertically integrated stack, pricing is fully consolidated at a flat rate of $4.50 per hour. This provides predictable, all-in-one billing that simplifies planning and scales with usage.
