When monitoring escalating geopolitical tensions, intelligence analysts face a fundamental challenge: distinguishing signal from noise before decision advantage is lost. In early June 2025, as Israel-Iran tensions reached a critical threshold, Seerist’s Intelligence Team leveraged Seerist’s AI-driven platform to provide clients with advance warning of the potential for kinetic operations and maintained continuous situational awareness through 10 days of active conflict. This experience documents that operational workflow.
In early June 2025, there were an increasing number of signs pointing to Israel taking preemptive military action against Iran. With nuclear negotiations faltering, Israel was seemingly presented with an opportune moment to counter a strategic adversary. Concessions on uranium enrichment were the biggest sticking point, progress was lacking, and both U.S. and Israeli patience appeared to be waning. One such signal that initially seemed to bolster the likelihood of hostile actions was the U.S. State Department's announcement calling for the ordered departure of non-essential personnel from key locations across the Middle East.
Official releases from government officials are only one small piece of the indications and warnings (I&W) pie. From an intelligence perspective, the challenge is always multi-fold:
What indicators provide the earliest detection that may signal a shift toward offensive hostilities?
Do analysts have access to sources and technologies that can best surface these indicators, track conflict evolution, and monitor risk across local, regional, and global dimensions?
How can analysts visualize complex information streams to communicate relevant, actionable intelligence to stakeholders in a clear and concise manner?
For an analyst, the goal is always to cut through the noise, what Carl von Clausewitz would call the 'fog of war', to surface the most relevant and impactful information before it becomes stale and the decision advantage is lost.
No matter the sector, the Intelligence Cycle provides a useful framework for structuring the approach to most analytical tasks. Unlocking the potential of AI-driven intelligence, to more effectively cut through the noise of billions of raw data points to surface the signals that matter, means the analyst needs to set clear priorities early.
Early Warning: Understanding the Threat Landscape
AI-Driven Human Validated
Dissemination + Integration
Planning + Tasking
Collection
Processing + Exploitation
Analysis + Production
Intelligence Cycle
Step 1
Intelligence priorities focused on conflict outbreak indicators, strike verification, retaliation warning signs, and regional spillover risk.
Step 2
Human-curated sources to provide comprehensive coverage at global, regional, and local levels.
According to the US government, step one of the intelligence cycle (planning and tasking) asks decision-makers and key stakeholders to determine what issues need to be addressed and to set intelligence priorities. Those issues and information requirements, in turn, guide any organization's collections strategy (step two) to drive appropriate analysis and production requirements.
Step 1: Seerist Intelligence Team's "Planning & Tasking". Closely identify, monitor, and communicate incidents of importance that align with Seerist's events methodology related to the outbreak and evolution of conflict between Israel, Iran, and other potential stakeholders.
Step 2: Human-curated Collections Strategy. Seerist boasts a Research & Collections team comprised of professionals with deep regional, linguistic, and cross-sector expertise. This team continuously surfaces, evaluates, and integrates data streams (news and social) onto the platform driven by information requirements and refined by client priorities. All sources targeted for integration onto the platform are curated to ensure the data that is processed by select AI models is relevant and specific to mission needs.
Back on June 12, 2025, there were early indications that conflict might be imminent. One of the indicators was a marked shift in the volume of news reporting clustered around perceived tensions over the status of Iranian nuclear program negotiations. Another indicator was the number of those reports where the emotions of "fear" and "anger" (Figure 1) pointed to an accelerating narrative where Israel was primed to launch preemptive strikes on Iran.
Pre-Conflict Indicators: June 11-12, 2025
Figure 1. Seerist's sentiment and emotions AI models indicated a spike in fear that corresponded with the June 11th ordered departure of non-essential U.S. personnel from the Middle East
AI-Driven Human Validated
Intelligence Cycle
Dissemination + Integration
Planning + Tasking
Collection
Processing + Exploitation
Analysis + Production
Step 3
AI models process and categorized high volumes of news and social content, analyzed sentiment, emotions, and integrated human-driven source reliability ratings.
Leveraging specific AI models, the Seerist Intelligence Team could more efficiently sift through and visualize trends across myriad news and social sources in one central area to understand strike-centric narratives, and whether they were accelerating and pointing toward a tipping point in the conflict (Figure 2).
However, a key consideration in truly sparking (and holding) the interest of any analyst when it comes to new AI capabilities is designing technology that integrates seamlessly with workflows.
Figure 2. Seerist's DiscoverAI highlighted increasing volumes of news reporting related to rising tensions over Iran's nuclear program & corresponding threats of military action
From a workflow perspective, DiscoverAI utilizes AI techniques to pull in all related content into one single dashboard. A user can see what's accelerating and explore the full-spectrum of reporting on a topic: from the less curated, to the human-verified alerts with more metadata, to the professionalized long-form analytical pieces. A couple of clicks on the same screen to understand the bigger picture versus scouring through multiple sources on different tabs. This eliminated the 'tab proliferation' problem where analysts typically waste precious time switching between news aggregators, OSINT tools, and platforms.
Integrating the two information streams together painted a higher confidence picture of imminent conflict in the Levant region, and the need to shift the Intelligence Team's posture into one that could surge to meet the demands of a larger crisis. On the morning of June 13, following detection of a noticeable shift in sentiment, Israeli strikes commenced (Figure 3).
Workflow Integration: Connecting Tactical Data to Strategic Analysis
AI-Driven Human Validated
Intelligence Cycle
Dissemination + Integration
Planning + Tasking
Collection
Processing + Exploitation
Analysis + Production
Step 5
Client alerts, ‘Snippets’, and ‘Deep Dive’ reports delivered timely intelligence in multiple formats. Evacuation ratings provided actionable guidance to inform operational decisions. A constant feedback loop informed and refined Step 1.
Step 4
Human-driven analysis through outputs like Verified Events provided metadata and added context to world events, and Control Risks’ analysis offered in-depth expert interpretation.
Figure 3. Monitoring the early stages of the Israel-Iran Crisis
The morning of June 13, 2025, in the wake of an Israeli aerial campaign against dozens of targets related to Tehran's nuclear program and critical components of Iran's integrated air defense system, confirmed the shift from escalating diplomatic tensions into full-fledged kinetic operations. Iran's PulseAI score dropped 4.6 points between June 11-13, including a 1.7-point drop in the hours immediately following initial strikes — a quantitative indicator of a drop in Iran’s stability and the elevation of the country’s risk profile.
Active Monitoring: Real-Time Strike Verification and Pattern Analysis
Figure 4. Iran’s PulseAI score deteriorated quickly over two days (-4.6), with a -1.7 drop prior to the first Israeli strikes
Since pre-conflict I&W was already old news, the main priorities at this stage were to:
Identify and continue to verify Israeli strikes and activities targeting Iran.
Track I&W for signs of Iranian retaliation (e.g., Strait of Hormuz closure, use of Iranian-aligned proxy groups in the Middle East against Israel, the US, or other key stakeholders).
Surface, track, and communicate second and third order effects of the conflict in the region, and from a global perspective.
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Priority 1: Strike Verification and Pattern Recognition
To address the first priority, Seerist’s intelligence team leveraged OSINT techniques to verify kinetic activities against Iran. Integrating these strikes, what are called verified events, onto the platform helped the team to visualize strike patterns that could later drive impact assessments (i.e., number of casualties, damage to critical infrastructure). These verified events helped to corroborate the deluge of information flowing in via news and social from Iran detailing strikes in key locations in Tehran and Natanz.
Seerist’s Intelligence Team geolocated and verified 28 kinetic strikes within the first 18 hours of operations using multi-source OSINT verification (Figure 5). Each Verified Event, which includes higher fidelity metadata, was published to the platform within hours of open-source reporting (Figure 6).
One of the biggest challenges an analyst faces after sifting through thousands of data points trying to find the most relevant information is the need to get deeper context…quickly. In this instance, that meant the need to connect accelerating news around Iran-Israel tensions to the relevant longer-form analysis written by Control Risks’ subject matter experts. These experts provided an added layer of context to the dynamic situation, honed through decades of on-the-ground regional experience. The human-curated analysis from Control Risks corroborated what Seerist's Intelligence Team were seeing in the news and social landscape: "enrichment remained the biggest sticking point", and "Israel [was] aware that it [had] an opportune moment to counter a strategic adversary, and events suggest[ed] planning for an attack, if not the operationalizing of a plan, [were] at an advanced stage."
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Figure 5. Heat mapping of 28 ‘War’ Verified Events in Iran from 12-13 June
Click green buttons to view Verified Events.
Figure 6. Verified Events showing Israeli kinetic strikes targeting key components of Iran’s nuclear infrastructure
Priority 2: Iranian Retaliation Indicators
The second priority focused on tracking the scope, scale, and target location of Iran’s retaliation. Key questions included whether Iran would limit its response to Israeli targets or expand operations to U.S. military assets in the region.
Tracking retaliation required continuous monitoring across multiple threat vectors. The Intelligence Team used DiscoverAI to identify emerging narratives around Iranian response options, further reducing the noise by filtering outputs with keywords related to “Strait of Hormuz closure”, “Iranian-aligned proxy mobilization”, and “military retaliation”. The platform’s timeline visualization enabled analysts to see how the conflict evolved from defensive posturing on June 13 to more explicit threats against civilian and economic infrastructure by June 14.
Ultimately, Iran responded with a 100-drone barrage on June 13, followed by escalation to economic targets in the days immediately after. By June 14-15, EventsAI and Verified Events showed both countries had escalated beyond military targets to economic infrastructure, with reporting showing strikes on oil refineries, fuel depots, and energy facilities accelerating sharply (Figures 7, 8).
Iranian missiles struck the Haifa oil refinery (processing 197,000 bpd, 70% for domestic consumption).
Israeli strikes hit Iran's Shahran fuel depot, Shahr Rey refinery, and partially suspended production at South Pars gas field, the world's largest gas field and source of Iran's domestic natural gas supply.
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Figure 7. Verified Events showing Iran’s targeting of Israeli critical infrastructure in Haifa, specifically the city’s power supply and a key refinery
Figure 8. Verified Events indicating Israel’s targeting of Iran’s oil and gas infrastructure
While the AI-driven outputs helped flag accelerating volumes of reporting on oil and gas infrastructure, human verification remained critical. This required the Intelligence Team to cross-reference sources to refine metadata (geocoding, sector impacted, attack type), leverage multi-lingual capabilities to extract context and deeper understanding from local sources, and integrate Control Risks’ assessment of Iran’s strategic calculus before confirming a shift in Tehran’s priorities (i.e., contain the bilateral conflict or escalate regionally).
The shift to economic infrastructure carried immediate implications for clients with regional exposure. Energy sector companies operating in Israel faced direct facility risk. Shipping operators transiting the Eastern Mediterranean, Red Sea, and Gulf of Aden needed to consider risk appetite when planning their routes. Airlines operating in the region also had to determine the flight risk and potential likelihood of losing an aircraft and passengers to misidentification by stressed air defense operators in Iran or Israel. The Intelligence Team’s ability to detect and verify targeting patterns within hours, rather than days, enabled clients to mitigate financial, operational, and reputational risk earlier.
Priority 3: Spillover Assessment and Regional Impact
The third priority centered on detecting regional spillover beyond what to that point had been a bilateral exchange between Israel and Iran. Between June 15-21, Seerist's Intelligence Team maintained continuous monitoring for spillover indicators. By June 22, spillover concerns materialized when Iranian state media quoted MP Esmail Kosari (also a commander in the Islamic Revolutionary Guard Corps) as saying the legislature had agreed to close the Strait of Hormuz, with the final decision resting with Iran's Supreme National Security Council.
When Kosari’s statement emerged, DiscoverAI (Figure 9) automatically clustered related content into one single space that brought in EventsAI – news and social processed by AI models (Figure 10), Verified Events that tracked activities near the Strait of Hormuz, and Control Risks’ analysis that provided strategic context on historical closure threats. This integration meant analysts spent minutes, not hours, moving from raw reporting to contextualized intelligence.
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Figure 9. DiscoverAI headline tracking Strait of Hormuz tensions
Figure 10. Spike in “Fear” around rising tensions in the Strait of Hormuz and its impact on global energy supply chains
Control Risks assessed that the statement did not immediately increase the likelihood of the Strait of Hormuz’s closure, noting the most immediate threat remained limited to U.S.- and Israel-affiliated vessels, including approximately 60-80 U.S. Navy vessels at sea in the region. All commercial vessels in the area were assessed to be at increased risk of collateral damage during any Iran-U.S. engagements on the water.
For analysts reporting on the Strait of Hormuz’s closure risk, credibility depended on more than just detecting the threat. It required explaining how likely such a scenario was. That’s where the integration of source reliability ratings and in-depth, historical stakeholder assessments, both curated by human experts, were critical. Rather than asking leadership to trust an opaque AI-generated risk score, analysts were better positioned to walk through sourcing and reasoning that supported an ‘elevated risk, but low likelihood’ assessment.
Based on this 10-day operational cycle monitoring the Israel-Iran conflict, the Seerist platform demonstrated several key capabilities:
What the Fusion of AI-Driven Technology and Human Analytical Expertise Enabled
Multi-source Integration
Sentiment and Emotion Analysis
Verified Events
Expert Analysis Integration
EventsAI aggregated and analyzed news and social media content across myriad languages and sources
DiscoverAI compiled related stories under unified headlines, connecting Breaking Events, Control Risks’ analysis, and Verified Events into a single interface
Source reliability ratings (high, medium, low, not rated) enabled analysts to evaluate information quality to understand different narratives from varying perspectives
Multi-source Integration
EventsAI detected sentiment shifts and emotion patterns (fear, anger, sadness) across different language sources
Emotion modeling showed declining fear levels among Israeli sources corresponding with successful missile interceptions
Regional language sources showed sustained anger and sadness despite declining fear as the conflict advanced
Sentiment and Emotion Analysis
Human analysts geolocated and verified 28 kinetic strikes during the first 24 hours of the conflict
Heat mapping visualized strike patterns against key Iranian military and nuclear facilities
Attack type and sector analysis revealed operational patterns
Verified Events
Control Risks’ analysis provided strategic context on conflict scenarios, regional dynamics, and risk assessments
Scenario modeling (Most Likely and Credible Alternative) framed potential conflict trajectories
Evacuation Ratings translated risk assessments into actionable guidance
Expert Analysis Integration
Workflow Design
Seerist’s single DiscoverAI dashboard consolidated multiple information streams
Filtering by source type, reliability, language, and event category enabled targeted analysis
Visual representations (charts, heat maps, timelines) aided pattern recognition
Workflow Design
Analysis of the Strait of Hormuz situation ultimately prompted an updated "Credible Alternative" scenario for regional conflict evolution. In this scenario, the Iranian response to U.S. strikes on its nuclear facilities would be escalatory and trigger the targeting of U.S. bases in the Gulf and use of Iranian-aligned actors in Iraq to harass U.S. military and diplomatic assets. Also in this alternative scenario, Tehran would take measures to disrupt maritime traffic through the Strait of Hormuz to increase economic pressure by driving oil prices up.
The threat in the Strait of Hormuz illustrated how continuous monitoring enabled dynamic risk assessment updates as new indicators emerged over the 10-day conflict period. Extracting these insights purely from AI-enabled technology was possible, but the true force multiplier was the pairing of these curated data points, shaped and refined by human analytical expertise, to generate higher confidence intelligence. Intelligence that more effectively informed the decision-making calculus of leaders in a high-pressure situation.
For analysts reporting on the Strait of Hormuz’s closure risk, credibility depended on more than just detecting the threat. It required explaining how likely such a scenario was.
The 10-day Israel-Iran conflict cycle demonstrated that modern intelligence advantage comes from processing signal faster without sacrificing credibility. This required solving three problems simultaneously: maintaining transparency about sourcing and reasoning, keeping analysts in control of critical judgments, and integrating tools seamlessly into crisis workflows.
The Israel-Iran conflict validated that AI doesn't replace analytical judgment when properly designed around transparency, control, and workflow integration. It ensures analysis operates on complete, timely, defensible information rather than delayed, fragmented reporting. The difference between drowning in information and delivering intelligence leadership can act on comes down to design philosophy: tools built for analysts, not tools that ask analysts to adapt.
Post-Conflict Takeaways
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Leveraging AI to Navigate the Complexities of the 2025 Israel-Iran Conflict
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