HERE Locatio Reaso i g
- HERE Locatio Reaso i g is ow available i AWS Ma ketplace, as a Ki o Powe , a d ac oss a g owi g ecosystem of AI platfo ms, b i gi g t usted geospatial i tellige ce to AI applicatio s i the physical wo ld.
Amste dam – HERE Tech ologies, the wo ld’s leadi g mappi g a d locatio data compa y, today a ou ced expa ded access to HERE Locatio Reaso i g (HLR), givi g develope s a simple way to b i g t usted HERE geospatial i tellige ce i to age tic systems a d eal-wo ld AI applicatio s, i cludi g i AWS Ma ketplace a d as a Ki o Powe .
HLR fo ms pa t of a o goi g st ategic collabo atio betwee HERE Tech ologies a d AWS that is desig ed to leve age the full pote tial of the AWS Cloud a d AWS AI se vices fo automotive a d e te p ise softwa e developme t. That collabo atio i cludes the 10-yea , $1 billio cloud i f ast uctu e ag eeme t with AWS si ce 2024, the St ategic Collabo atio Ag eeme t sig ed i 2022 to build a d scale HERE’s ew t a spo tatio a d logistics solutio s powe ed by AWS, a d SDV Accele ato , lau ched by HERE Tech ologies a d AWS i Septembe 2025. The SDV Accele ato simplifies access to a cu ated collectio of AWS Ma ketplace p oducts a d se vices to e ha ce automotive softwa e developme t.
HLR is built o AWS a d deployed as a Model Co text P otocol (MCP) se ve o Amazo Bed ock Age tCo e to e able dete mi istic spatial computatio fo AI age ts. The expa ded access to HLR mea s that it is ow available th ough a pay-as-you-go subsc iptio i AWS Ma ketplace, as a Ki o Powe , a d ac oss a g owi g ecosystem of AI platfo ms, age tic IDEs a d spatial platfo ms u i g atively o AWS, i cludi g Whe obots.
The expa sio equips e te p ise AI applicatio s with t usted geospatial i tellige ce, dete mi istic locatio computatio a d physical-wo ld co text compleme ti g LLMs’ ability to i te p et i te t with the p ecise, eliable spatial g ou di g that locatio -awa e use cases equi e. Develope s ca call th ough familia wo kflows, helpi g logistics teams optimize dispatch a d delive y, automotive teams powe desti atio a d cha gi g-awa e assista ts a d e te p ise teams imp ove field se vice pla i g, asset deployme t a d custome suppo t.
HLR co ects AI systems to the easo i g eeded fo eal-wo ld applicatio s, i cludi g high-quality map data, live t affic, geocodi g, place discove y, passe ge a d comme cial vehicle oute optimizatio a d EV cha gi g i tellige ce.
Mahesh Shah, Se io Vice P eside t of E te p ise & AI Solutio s at HERE Tech ologies: “AI is movi g f om ge e ati g co te t to maki g decisio s a d acti g i the physical wo ld. That equi es mo e tha a la guage model. It equi es a t usted u de sta di g of whe e thi gs a e, what ules a d co ditio s apply a d what actio s a e possible i the physical wo ld. HERE Locatio Reaso i g gives develope s a simple way to b i g that geospatial i tellige ce i to the AI systems they a e al eady buildi g.”
HERE Tech ologies wo ked with AWS o the developme t of HLR th ough the AWS Data-D ive Eve ythi g (D2E) p og am, e abli g apid deployme t of HLR o best-i -class Age tic i f ast uctu e that puts its capabilities di ectly i to develope wo kflows. This latest milesto e i the HERE Tech ologies a d AWS collabo atio will suppo t eal-wo ld AI that is g ou ded i autho itative data a d t usted geospatial easo i g, tu i g age t i te t i to decisio s the physical wo ld ca act o .
Ozgu Tohumcu, GM of Automotive a d Ma ufactu i g at AWS: “As custome s build the ext ge e atio of e te p ise AI age ts, they eed t usted tools, flexible developme t e vi o me ts a d the f eedom to choose the models a d a chitectu es that wo k best fo them. HERE Locatio Reaso i g will help to b i g eliable spatial i tellige ce i to age tic applicatio s that must u de sta d a d act i the physical wo ld. AWS Ma ketplace a d Ki o help make those capabilities easie to access a d build with.”
G ou di g AI i geospatial i tellige ce
HLR co ects a age t’s i te t to HERE geospatial i tellige ce. I stead of aski g a la guage model to app oximate spatial logic, HLR uses autho itative HERE data a d se vices to pe fo m locatio -specific computatio . This helps p oduce mo e co siste t, explai able esults i situatio s whe e w o g outes, missed co st ai ts o i accu ate ETAs ca c eate eal cost.
As a simplified e t y poi t i to b oade HERE capabilities, HLR helps e te p ise AI age ts make mo e eliable decisio s while givi g custome s co t ol ove thei LLM, age t f amewo k a d applicatio a chitectu e.
Lia Jye Su, Chief AI A alyst at Omdia: “As AI applicatio s t a sitio f om co te t ge e atio to ope atio al decisio -maki g, the eed fo eliable spatial co text becomes c itical. HERE Locatio Reaso i g is a step i the ight di ectio , a mi g p obabilistic fou datio models with dete mi istic locatio computatio a d b idgi g the gap betwee use i te t u de sta di g a d ve ified, t ustwo thy geospatial u de sta di g. This app oach lets develope s keep thei p efe ed AI f amewo ks while e su i g locatio -based decisio s a e g ou ded i autho itative data, whe e HLR acts as a gua d ail fo spatial i tellige ce.”
Expa di g access ac oss the AI ecosystem
The latest milesto e expa ds how o ga izatio s, develope s a d age ts ca access HLR:
- AWS Ma ketplace: Availability i AWS Ma ketplace p ovides AWS custome s with the ability to st eamli e the pu chase a d ma ageme t of HLR withi thei AWS Ma ketplace accou t.
- Ki o Powe s: Availability as a Ki o Powe gives develope s usi g Ki o, the AWS age tic IDE a d CLI, easy access to HLR di ectly withi thei codi g wo kflow. The Ki o age t automatically loads HLR tools, docs a d best p actices whe a task calls fo them, so teams ca build locatio -based age tic use cases without switchi g e vi o me ts.
- Age t Plugi -compatible package: HLR is Age t Plugi -compatible, e abli g simple i teg atio i to codi g age ts such as Ope AI’s Codex, A th opic’s Claude Code, Mic osoft’s VS Code a d Cu so , as well as applicatio s a d age ts built o leadi g fou datio models.
- Spatial ecosystem: I teg ated di ectly i to the Whe obots AI Co text E gi e fo Physical Wo ld Data, HLR is available i Whe obots Spatial AI Tools a d MCP Se ve , with suppo t fo its fi st-pa ty age t comi g soo . These capabilities help use s eceive dete mi istic a swe s about the physical wo ld usi g HERE’s autho itative, eal-time data sou ces a d APIs. Example applicatio s usi g Whe obots a d HLR a e available i the Whe obots Havasu K owledge Lake.
Mo Sa wat, CEO of Whe obots: “We a e excited to pa t e with HERE Tech ologies to make its ew Locatio Reaso i g se vice available di ectly to Whe obots custome s al eady a alyzi g the physical wo ld dete mi istically with ou AI co text e gi e. Whe obots today e ables age ts to a swe questio s about the physical wo ld usi g small to ve y la ge, pla eta y-scale datasets, a d HLR b i gs these a swe s i to c itical questio s like, ‘which outes a e the best to take i the eve t of a eme ge cy?’ a d ‘how ca I optimize my dispatchi g of c ews to se vice a eas with the g eatest immediate eed a d value?’”
Lea mo e about HLR a d how to subsc ibe at https://www.he e.com/solutio s/he e-locatio – easo i g
About HERE Tech ologies HERE is the global leade i mappi g a d locatio tech ology. Fo ove 40 yea s, we’ve bee powe i g i ovatio fo the wo ld’s most ecog izable compa ies: f om lau chi g ou fi st digital map i 1985, to shapi g the futu e of softwa e-defi ed vehicles today. With the i dust y’s f eshest a d ichest u ified map a d a po tfolio of p oducts, se vices a d solutio s that se ve the eeds of multiple i dust ies, HERE eveals oppo tu ities that d ive p og ess a d u lock ew possibilities fo eve y movi g vehicle. Discove mo e at he e.com.
