Learn how Seismic’s AI-powered enablement, training, and coaching solution enables sales and marketing teams to engage buyers and grow revenue.
Seismic is generally praised for its robust AI capabilities, particularly in enhancing productivity and streamlining workflows with its intuitive interface. Key complaints revolve around the software's learning curve and occasional technical glitches that can disrupt usage. The pricing is often seen as quite high, which can be a deterrent for smaller businesses. Overall, Seismic maintains a strong reputation for its advanced features and effectiveness in enterprise environments, despite some areas needing improvement.
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Seismic is generally praised for its robust AI capabilities, particularly in enhancing productivity and streamlining workflows with its intuitive interface. Key complaints revolve around the software's learning curve and occasional technical glitches that can disrupt usage. The pricing is often seen as quite high, which can be a deterrent for smaller businesses. Overall, Seismic maintains a strong reputation for its advanced features and effectiveness in enterprise environments, despite some areas needing improvement.
Features
Use Cases
Industry
information technology & services
Employees
1,500
Funding Stage
Debt Financing
Total Funding
$512.4M
AI Infrastructure Has a Physical Weak Spot Nobody Talks About Enough - Copper Supply Shocks
Something interesting happened this week that barely crossed into mainstream AI discussion. A strong earthquake in Chile disrupted copper ore production and pushed copper prices higher again. Chile matters because it produces roughly 24% of the world’s copper supply, and a huge part of global AI infrastructure indirectly depends on that metal. That connection is becoming impossible to ignore. Everyone talks about GPUs, compute scaling, inference costs, and power demand. But very few people talk about the raw materials underneath the entire AI stack. Copper is everywhere inside AI infrastructure: * data center power systems * transformers * cooling systems * switchgear * high-voltage cabling * backup energy systems * grid expansion * GPU interconnect infrastructure A single hyperscale AI data center can reportedly consume tens of thousands of tonnes of copper depending on scale and power architecture. At the same time, global copper supply is getting tighter: * new mines can take 15-20+ years to develop * major deposits are aging * permitting remains difficult globally * geopolitical risk keeps increasing * now even earthquakes are disrupting supply chains This is where the story becomes interesting from an AI perspective. AI demand growth is exponential. Copper supply growth is not. That mismatch is why more people are suddenly watching early-stage copper exploration companies again. One example is NovаRed Mining Inc. and its Wilmac Copper-Gold Project in British Columbia. Not because it is producing copper today - it is not. But because markets are starting to realize future AI infrastructure may require entirely new copper discoveries. Some interesting details about Wіlmac: * 16,078 hectares in BC’s Quesnel porphyry belt * located near Hudbay’s Copper Mountain Mine * soil results up to 1,125 ppm copper * interpreted intrusive centers identified * recent IP/AMT geophysics added deeper targeting data * company also pushing an AI-assisted targeting platform called MetalCore The bigger point is not "this stock goes up." The bigger point is that AI is no longer just a software story. It is becoming a materials story. And every supply disruption - whether geopolitical, regulatory, or seismic - reminds the market that physical infrastructure still matters. The AI boom may eventually depend just as much on copper supply chains as on semiconductor innovation itself. NFA.
View originalPricing found: $1.8, $1.5
AI Infrastructure Has a Physical Weak Spot Nobody Talks About Enough - Copper Supply Shocks
Something interesting happened this week that barely crossed into mainstream AI discussion. A strong earthquake in Chile disrupted copper ore production and pushed copper prices higher again. Chile matters because it produces roughly 24% of the world’s copper supply, and a huge part of global AI infrastructure indirectly depends on that metal. That connection is becoming impossible to ignore. Everyone talks about GPUs, compute scaling, inference costs, and power demand. But very few people talk about the raw materials underneath the entire AI stack. Copper is everywhere inside AI infrastructure: * data center power systems * transformers * cooling systems * switchgear * high-voltage cabling * backup energy systems * grid expansion * GPU interconnect infrastructure A single hyperscale AI data center can reportedly consume tens of thousands of tonnes of copper depending on scale and power architecture. At the same time, global copper supply is getting tighter: * new mines can take 15-20+ years to develop * major deposits are aging * permitting remains difficult globally * geopolitical risk keeps increasing * now even earthquakes are disrupting supply chains This is where the story becomes interesting from an AI perspective. AI demand growth is exponential. Copper supply growth is not. That mismatch is why more people are suddenly watching early-stage copper exploration companies again. One example is NovаRed Mining Inc. and its Wilmac Copper-Gold Project in British Columbia. Not because it is producing copper today - it is not. But because markets are starting to realize future AI infrastructure may require entirely new copper discoveries. Some interesting details about Wіlmac: * 16,078 hectares in BC’s Quesnel porphyry belt * located near Hudbay’s Copper Mountain Mine * soil results up to 1,125 ppm copper * interpreted intrusive centers identified * recent IP/AMT geophysics added deeper targeting data * company also pushing an AI-assisted targeting platform called MetalCore The bigger point is not "this stock goes up." The bigger point is that AI is no longer just a software story. It is becoming a materials story. And every supply disruption - whether geopolitical, regulatory, or seismic - reminds the market that physical infrastructure still matters. The AI boom may eventually depend just as much on copper supply chains as on semiconductor innovation itself. NFA.
View originalI made GODS eye , satellite intelligence tool to watch us, Iran conflicts and other interesting stuff.
I stopped overthinking and just vibecoded this in a day using Claude and GitHub copilot. It’s insane guys GOD’S EYE ( an advanced satellite intelligence tool) It’s basically one map, but stacked with live global data: • Aircraft tracking (ADS-B) → see commercial + military flights moving in real time • Ship tracking (AIS) → global maritime traffic, choke points, weird patterns • Satellite imagery → scroll dates, compare before/after, NDVI, thermal, etc. • Fires → live wildfire detection (NASA FIRMS) • Earthquakes → real-time seismic feed • Natural events → storms, floods, volcanoes (EONET) • Weather → live + forecast • Air quality → PM2.5, NO₂, ozone • Satellite orbits → see what’s literally above you • News → global events mapped by location • Search → jump anywhere on earth instantly No magic. Just stitched everything together into one view. Now the uncomfortable part: We’re watching global conflicts using the same kind of data this pulls in. Right now: • The US and Iran are in active conflict after strikes started in Feb 2026 • The Strait of Hormuz is disrupted, affecting \~20% of global oil flow • Iran is using fast attack boats and asymmetric tactics that are hard to track • Peace talks just failed after 21 hours, so this isn’t cooling down And here’s the weird realization: Most of what analysts, journalists, even governments watch… isn’t some secret system. It’s variations of: satellite imagery, ADS-B, AIS, weather + signals The difference is not access. It’s who puts it together cleanly. That’s literally what this tool is. https://godeye.up.railway.app/ If you think this is good, then I can buy a domain and host this for you all. submitted by /u/IngenuityFlimsy1206 [link] [comments]
View originalPricing found: $1.8, $1.5
Key features include: Loading component..., Platform, How We Help, What We Do, Capabilities, For Teams, For Industries, Use Cases.
Seismic is commonly used for: Sales training and onboarding for new team members, Real-time content recommendations during client meetings, Performance analytics for sales teams to identify strengths and weaknesses, Personalized coaching for sales representatives based on AI insights, Content management and distribution for marketing teams, Automated reporting and forecasting for revenue leaders.
Seismic integrates with: Salesforce, HubSpot, Microsoft Teams, Slack, Zoom, Google Workspace, Marketo, LinkedIn Sales Navigator, Pipedrive, Oracle CRM.
MIT Tech Review AI
Publication at MIT Technology Review
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