Swarm Engineering transforms uncertainty into smarter, faster decisions, optimizing supply chain, logistics, workforce planning, and demand forecasting with AI.

Joined December 2016
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#GEAPS2026 wasnโ€™t about AI hype. It was about margin discipline in a volatile grain system. Grading precision. Infrastructure limits. Decision velocity. In grain, small inconsistencies compound fast. At SWARM, we scale operator judgment so better decisions happen under pressure. linkedin.com/posts/swarm-engโ€ฆ #GrainIndustry #DecisionIntelligence
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We made a video about a cotton operation and the decision architecture gap it was running into. The problem isn't specific to cotton, it's the condition of every agrifood commodity operation running on disconnected systems and batch update cycles. The data is there. The timing is wrong an the decision cannot wait. In #cotton, that gap costs you when the price window closes before your inventory position is confirmed. In grain, when the spot market moves faster than your scheduling cycle. In feed, when the formulation decision runs on yesterday's ingredient costs. Watch the video. If you recognize your operation in it, send us a message. linkedin.com/posts/swarm-engโ€ฆ
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The compliance update landed Friday. Production found out Tuesday. The cost was already in the schedule. Four days. Three active production runs affected. Materials staged. Customer window locked. Team absorbed it in overtime and expedited sourcing. Nothing on the risk log. Nothing flagged as an incident. Just the week. Compliance latency is the most consistent and least discussed cost in food processing. Not because teams are careless. Because there's no automated bridge between when a regulation changes and when the operation knows to act. How does your operation find out?
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In agrifood, compliance doesn't break because teams miss regulations. It breaks because they see them too late. A change publishes. It moves through email digests, consultant queues, review cycles. By the time it reaches the operation, production has already moved. That gap is measured in days. That's where avoidable cost accumulates. SWARM AVA monitors your regulatory environment continuously and surfaces changes the moment they happen - with operational context already attached. Not a general alert. A specific signal: what changed, which production run is affected, what decision needs to be made. The compliance team still owns the review. What changes is everything before it. Gap shrinks from days to hours. Already live inside the #AAFCO Member Portal. Deployed in feed manufacturing and food processing operations. If your compliance process still runs on scheduled review cycles, the question isn't whether there's delay. It's how much it's costing you.
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The challenge isn't just moving goods. It's deciding how to move them under uncertainty. @ShailKhiyara nails it with insights from @BNSFRailway #Grain #SupplyChain @NGFA
This morning in #Nashville, just outside the venue where #NGFA had brought together #CEOs, #COOs, and #operators from across the grain industry, I saw a sight I don't often get to see in #SanFrancisco. @SWARMeng @NGFA #Grain linkedin.com/posts/shailkhiyโ€ฆ
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Resilience Isnโ€™t About Absorbing Shocks Anymore, Itโ€™s About Outpacing Them For years, โ€œ#resilienceโ€ in #supplychains meant the ability to take a hit and keep moving. But 2026 has rewritten the definition. Across agrifood and industrial operations, volatility is no longer episodic itโ€™s structural. Climate disruptions, fragmented trade routes, labor shortages, tariff swings, and transportation bottlenecks arenโ€™t anomalies; theyโ€™re the operating environment. linkedin.com/pulse/resiliencโ€ฆ
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from our #CEO @ShailKhiyara Prediction is not a decision. For the past few years, enterprise AI has been obsessed with prediction. Every board deck celebrates forecast accuracy. Demand models get tuned to the second decimal point. Teams argue over whether the signal is 91 percent or 93 percent accurate, as if those two points determine survival. bit.ly/3ORiV23
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๐Ÿฎ๐Ÿฌ๐Ÿฎ๐Ÿฒ ๐—ถ๐˜€ ๐˜๐—ต๐—ฒ ๐˜†๐—ฒ๐—ฎ๐—ฟ ๐—ฎ๐—ด๐—ฟ๐—ถ๐—ณ๐—ผ๐—ผ๐—ฑ ๐—ผ๐—ฝ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—บ๐—ผ๐˜ƒ๐—ฒ ๐—ฏ๐—ฒ๐˜†๐—ผ๐—ป๐—ฑ ๐˜ƒ๐—ถ๐˜€๐—ถ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐˜† ๐˜๐—ผ ๐˜๐—ผ๐˜๐—ฎ๐—น ๐—ผ๐—ฟ๐—ฐ๐—ต๐—ฒ๐˜€๐˜๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป. Predicting the future isn't enough when your margins are at stake. In 2026, the industry leaders aren't just watching data, they are using it to ๐—ผ๐—ฝ๐˜๐—ถ๐—บ๐—ถ๐˜‡๐—ฒ ๐—ฒ๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—ฑ๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป in real time. linkedin.com/posts/swarm-engโ€ฆ
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Insights on the #GrainIndustry, #AI & margin pressures. linkedin.com/in/shailkhiyaraโ€ฆ
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๐—ช๐—ต๐—ฒ๐—ป ๐——๐—ฒ๐˜๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—ข๐˜‚๐˜๐—ฝ๐—ฎ๐—ฐ๐—ฒ๐˜€ ๐—ง๐—ฟ๐˜‚๐˜€๐˜ ๐—ถ๐—ป ๐˜๐—ต๐—ฒ ๐—™๐—ผ๐—ผ๐—ฑ ๐—ฆ๐˜†๐˜€๐˜๐—ฒ๐—บ ๐˜ž๐˜ฉ๐˜บ ๐˜จ๐˜ญ๐˜บ๐˜ฑ๐˜ฉ๐˜ฐ๐˜ด๐˜ข๐˜ต๐˜ฆ ๐˜ฉ๐˜ฆ๐˜ข๐˜ฅ๐˜ญ๐˜ช๐˜ฏ๐˜ฆ๐˜ด ๐˜ณ๐˜ฆ๐˜ท๐˜ฆ๐˜ข๐˜ญ ๐˜ข ๐˜ฅ๐˜ฆ๐˜ฆ๐˜ฑ๐˜ฆ๐˜ณ ๐˜ง๐˜ณ๐˜ข๐˜ค๐˜ต๐˜ถ๐˜ณ๐˜ฆ ๐˜ฃ๐˜ฆ๐˜ต๐˜ธ๐˜ฆ๐˜ฆ๐˜ฏ ๐˜ด๐˜ค๐˜ช๐˜ฆ๐˜ฏ๐˜ค๐˜ฆ, ๐˜ณ๐˜ฆ๐˜จ๐˜ถ๐˜ญ๐˜ข๐˜ต๐˜ช๐˜ฐ๐˜ฏ, ๐˜ข๐˜ฏ๐˜ฅ ๐˜ฑ๐˜ถ๐˜ฃ๐˜ญ๐˜ช๐˜ค ๐˜ต๐˜ณ๐˜ถ๐˜ด๐˜ต ๐˜ช๐˜ฏ ๐˜ข๐˜จ๐˜ณ๐˜ช๐˜ค๐˜ถ๐˜ญ๐˜ต๐˜ถ๐˜ณ๐˜ฆ. The recent headlines about glyphosate residues in bread are not really about bread. linkedin.com/posts/shailkhiyโ€ฆ
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๐—˜๐˜ƒ๐—ฒ๐—ฟ๐˜† ๐—ผ๐—ฝ๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ต๐—ฎ๐˜€ ๐—ฎ ๐—ฏ๐—ฟ๐—ฒ๐—ฎ๐—ธ๐—ถ๐—ป๐—ด ๐—ฝ๐—ผ๐—ถ๐—ป๐˜. ๐—ฆ๐—ช๐—”๐—ฅ๐—  ๐—˜๐—ก๐—š๐—œ๐—ก๐—˜ ๐—บ๐—ฎ๐—ธ๐—ฒ๐˜€ ๐˜€๐˜‚๐—ฟ๐—ฒ ๐˜†๐—ผ๐˜‚ ๐—ป๐—ฒ๐˜ƒ๐—ฒ๐—ฟ ๐—ฟ๐—ฒ๐—ฎ๐—ฐ๐—ต ๐—ถ๐˜.โ€‹ SWARMโ€™s Agentic AI optimization engine turns multi-variable chaos into decisions that move at the speed of volatility. An operating system for #AgriFood resilience. #DecisionIntelligence #Optimization #SupplyChain #OperationalResilience linkedin.com/posts/swarm-engโ€ฆ
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๐—™๐—ฟ๐—ผ๐—บ ๐—ฆ๐—บ๐—ฎ๐—ฟ๐˜๐—ฒ๐—ฟ ๐— ๐—ผ๐—ฑ๐—ฒ๐—น๐˜€ ๐˜๐—ผ ๐—”๐—ฐ๐—ฐ๐—ผ๐˜‚๐—ป๐˜๐—ฎ๐—ฏ๐—น๐—ฒ ๐——๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป๐˜€ a brief look into new models and SWARMs #decision_intelligence bit.ly/4ajGW96
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From our #CEO. ๐—œ๐—ณ ๐—ฌ๐—ผ๐˜‚ ๐—–๐—ฎ๐—ปโ€™๐˜ ๐—ก๐—ฎ๐—บ๐—ฒ ๐˜๐—ต๐—ฒ ๐——๐—ฒ๐—ฐ๐—ถ๐˜€๐—ถ๐—ผ๐—ป, ๐—”๐—œ ๐—ช๐—ผ๐—ปโ€™๐˜ ๐—ฆ๐—ฎ๐˜ƒ๐—ฒ ๐—ฌ๐—ผ๐˜‚ The question is not โ€œIs this optimal?โ€ The question is โ€œDoes this hold up when reality shows up?โ€ Most AI systems collapse when volatility enters the room. linkedin.com/posts/shailkhiyโ€ฆ
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Spreadsheets are familiar. But familiarity is not a strategy. In volatile markets, manual tools create a false sense of control until reality hits. That is the Spreadsheet Trap. linkedin.com/pulse/breaking-โ€ฆ
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๐—ช๐—ต๐˜† ๐˜๐—ต๐—ฒ ๐—•๐—ฒ๐˜€๐˜ ๐—–๐—ฟ๐—ผ๐—ฝ ๐—ถ๐—ป ๐—ฎ ๐—š๐—ฒ๐—ป๐—ฒ๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—œ๐˜€ ๐—•๐—ฟ๐—ฒ๐—ฎ๐—ธ๐—ถ๐—ป๐—ด ๐—”๐—บ๐—ฒ๐—ฟ๐—ถ๐—ฐ๐—ฎโ€™๐˜€ ๐—™๐—ฎ๐—ฟ๐—บ ๐—˜๐—ฐ๐—ผ๐—ป๐—ผ๐—บ๐˜† - from our #CEO @ShailKhiyara Explore what happens when abundance becomes fragility, why digital twins are important and why the next revolution in food, business, and AI wonโ€™t come from more data - but from how we reason through it. linkedin.com/posts/shailkhiyโ€ฆ
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