Skip Navigation

The $190 billion rail industry is poised to grow at a steady pace of ~3% till 2023 across its key segments, such as rolling stock, rail control, services, and infrastructure. While these are statistics indicating quantitative growth, passenger experience is what makes train travel truly memorable, and is the key differentiator in the transportation world. The industry is therefore increasingly focusing on the principal drivers of digitalization, safety and security, and standardization and efficiency. It must address today’s and tomorrow’s needs while ensuring the sector’s raison d’etre of safety, reliability, and efficiency.

Digitalization in Rail

Build competitive advantage through innovation

Safety and Security

Enhance agility through ownership and execution

Standardization and Efficiency

Achieve cost assurance through capability and flexibility

Working closely with its customers, Cyient leverages technology and innovation to increase the pace of digitalization, improve safety and security, and build standardization and efficiency in rail operations. We enable global companies to achieve a competitive advantage with cost reduction and accelerated time-to-market.

Our vision is to apply technology imaginatively to solve problems that matter. Toward this end, we capitalize on our strong rail domain knowledge and experience gained globally in more than 350 major rail projects.  It may be about designing next-generation trains, enabling complex signaling upgrades, or improving efficiency through predictive maintenance, our 1,700+ engineers are at the core of addressing business challenges in the key rail segments we operate in:

 

cloud image
cloud image
cloud image
Strong experience inhigh-speed, metro, LRV,tram, and freight IRIS certifed Comprehensive experience, for e.g., in cab engineering and car body development IRSE licensedengineers eJzVfelaKrvS8HcD3AOoCMjQAzMqyiyKioKKIzbQKksmu2Htvc6P99q/JD2l5zSw3uHs57iATlcl lUqlqlKVCgbanXhpNB/w8WSC9vuCwYrAc8u5UPCjX/3NyWQlLgX4U/g24meyCRo0KjVzfbnhPS+I 4/ms4GfZBIMe1uHb4Q43HQv+2/mfiD8cAb92x8sJD34Xx58zbhJnEuLvz4iCDwCockvwmE1TdJpi cv5kIZ32ty9hA272mxPF8X/AYyaTzCXBb+X5ajYazz7L838LftrP+Fma9uch8rPxLS8aHycymWwu w2ToTJLJAeBMPp/IJVM0m6bpbCqX9efyiVSSSeZyuXQqn6PTAFB1PlxN+dmyLcyHvChW5pO5IBaw B/X5bCkW/LWPD4GL3/KfqwknYI+veH7Ej6wblZrpfn084QGlptzSzyQh3UpNhu2XV+PJ6Go1HfCA hkmGhT8n+wj5nch9AhKgz/DnbL85Bb90+OUSDBUggcO/bZTxDsPRw//CzwD3GM0jIPVrRAYrzBdT TvgWpWYSVfL5fCaZzObyjD+XTWQzNE2zTDLDJiFV4FtdfrqYgMlCxGVoOpH2p5IJFm9o87P8Phg4 ejfO5jMJOgcaMLkkQ4P5jrMZwESgH/lcHsxUDoDIpxN59AOTyeVTaX8yBTqJ3qEzOYaRYWqTxf8e 8/8U/FfzGS/RuSQsOxLvpFKASdBf6cntasILd7MxnKAM/CkvEfpyPuInoL36fn3CfYoKKRntr9Sg ywmf/BJw3XyyWqKVkFMwgIlscX/AApGhMdl+GczDDOCZLUF3++OP/m9p/fQ/lwUmKzXL968X/Kw7 v0dDiTOAMmw6j8+FPwlmiwaMTOfBnxzqUgbQW+0jo/2VEZcmS16YgXlTkP81TLXZqC9LBX6EY0sj bBCXQpUsYNk2YOJrYQzIUogzqTxgAjqbYCEfgjWbzGYlXm8I45HG6lnWn5P+oIlIQIaAPMHkWTrP 5kl/yaP/ZTNMOsekWJJfJKIBhliCQSmzyvYrl9gypBOXHTAuQIbKfAq5UoQSC847WJqT+af0TP2M noDXVwvfsy+Zp35W8yUvAlgT3p/PUJ8C95v3M2yOKo3GvACeiFRJAI+pypAfjScTjqpxw9WSp66W QHbw1LXSzEfdqW9wUhMOQaO44VgAC+Zjwv9LcVob6X0OAR8qwHn0po/ipVd57FVefXUsgR9LbcZY m7HaZobA+6i51HYutZ1jbedq27nUlZXUdCU1XWlNfdRKbTviPj95gRqBDvI8NQT0pkTA6hM4CpEf wiVJDVaTCb+kFpwAKbD4osAbU242GkwAlQQkGgG0ETWcL/4AVvxaUkBUjngoHCmpDyq6xGy+HPEf VKlGXYsTTvzyqT8twFY5Hc9WWiPl3z/8jJqujD/7TO2Uf+fC6IMHoMYzHn6ecuJwNYFflAYc+F3G /rPiRTjI0fyfGcX/O5xwU/QRcNd4yE3AC+pbH0C6jWfmbnyCXWfCT+dgh/5Yat8kSvCTyXgBRy4u uCFPlaTJKMnMJv9To+aQR2Yj0CWKn6J/ECMDEiOgyhcJJvqm/S79OBr/HkMGUYmm0vxR/QS2UWlG aythjnqKVorab/QNgfNRH2MwYJk9AGZqAfDMR5BB0Fxr62zAibzaQfQFNF1+zVciYBEfVcJYtIZ9 LkmcUVM7V5NI05R+b+Ls2lQbNaVG11KjawyeMu5rqcWd1OIOB3MnPRrBmQIqEYW9LU3ElBsKkN/B PoiacUO0IKQlLa1oH/W1mn1ywmo64VZLsA6BmP6mhhx4z9etITmdPu93RbChavtoUtq4arPhHCpW BX9fp9IYFJxnSv+Y0jeWto7ukwQYyEIFrL8rrPjunwXve2YyjLykgc6ZpABp+J8VNwFfMtR49gGW xvIPtuAgOVADIC+BPgloDb/4gLYH1x1Y98sxNxmNPz4oMK4p0oKohTAfrYZAKowBxCWUbwB8Lk9d T/lPzu9j8mkKCAG4hsAWmKW4BXjhX7kX+RxV5SdLzs8yKZlxwYL7Dz/75P1sioaNJ4CV+50/08F8 0qekf3UjT8u6ACBxG8wP3D18Vwsf0q3bkxV41BDmq0Vz9jH3hSVl/B6IM7CC/8OP/NeDX+AL0K2R EggIB2T67BN8V9skuPEi4ggObGMC75cegjfRV+Vf97er/AdQX7XXpV9rs9/8ZL7AwErt3OG1J9wM MAf6XQXXGoPNr80B8mgAYUN+2SOACHSMBdwBfivdMUB3aIA9ckfUAqLZCAD9Bvjun7nwrSLErKkE YBFnqJ1vfjn8MsKVf90MMuLGsThVX8d/acPVMpzwnT9gVySYuM4QakOCvyysxC9/dz6faGB1j9QZ lH9Gv8L2/ztwtNELs+sZ+PBlhUluYMQELATpnf+luNR3rPCAh/9XcFQ4oIkg9W08tEJj8VzFhz/z Nk1gRBOg14gqGumrBhqKKOk34mn3A50BLFQboeTYpvMPB5Z/azxwxAb7DfbIEVgWndV4yWs0mk8X 0Dni73xxCx4tdqVlRwWYRiYcti/F484bVl56Ak3t5R+wFfuoixlQQdEXfwEMfjYHlKKuuCnvj/mo zngKdkflKe2/9tGYOcn4e5xPsbNpf+8P+HIOPvwCP/0D7FD/pf/5lfaPwM+9W9SwB5Q0aY849PnB vvwB/rXogT/D/G/oBPs/24ln8Cu3mixfvXYDYEhkU/ks0Hgy4N9UPpMG9nEmm2fyKTbLpDOpVC6F fqHBs0yKTefy6Qy0s/M0k0pnmTydZpIZRh1OiXxsjM3YEO8BZtU4z5V92xywBIFBC7G2B1sek9HP hijY+4/P5H9rD33tstpZpU9eFlkLgMNn00QL1GCd1czQ0iNJJ4Bg/p/8MwBk+NEGuNxXxS1X5Zac L9inlO+AyeC3MTLlOOEP+s7QtJ9qgodhiMv/IflYgAQTOGidx38jxdY/4ID6NwSiKwbeCT9fAqNm NfVr7jfI13ezMTAoAENDuwfBY/wqbuRq8ddV8G1gl/FLP1wLElAmDTpyywM1H7yZ91/yYCO5RX0Y /wfNH4ZNeiNJ6964Xi0Xq6XLO9hgTZ1rcbPPFVTr2/MFlPqwPdW7bF2BQVnS7tAf/ncKTP0RHwfD EsYDYDmK8nslQeCkVn8bxBbgY62GX8CiFXiZXKxMLuUp/LP8s1D4YH8m9n9zgngIZl+Zdrzpb26y UtrC30WbdjOVC+SeiLpv/0epA/YdnoAwk/nwmx+RUEZpuSXGXHdcgzE65mEIxgaYA6wtaZG7jw9v vaXp35ASjCMliMY/5gYTnoTxXWf1f3ihD4GlO5/+raX+f0mKFX4TDw42JWflv8eHBZGDyiZUCcAS I2XHv74uQF/+F3Xlf5wsU37JjcAUbdqP/Ib92B3JmhEJn2ONYxZrNyX3ZTifCKoOVp7PgdbGTcai SjjpJ3Exl+FklVU7WowTssKXUfS9BTcaGYBNOfFb7VOp6S+tlnNVGZR7m0mnk2lVA8xDd95gzgkj /xCeQAOjYaDSwLUpdJLPDH2ADRfAwhf84ni6mnCa3slioIA9MhMXHJit4R8AZjzyi2oPMVBAQVUo 6x8DLZZb8qB/PNp7pcZpNsXm7PvI+gVFW3BtiY3Gta1GJMa2meNovmdAkZkDXf1Tcq8Q0VsdCw40 gxksHLCE/IClONHcDjdsAGJ4qOcHduH8mydsvOT/XSpjZiQubM/H8IC9r/NawwPzfmcILEuZmDk6 IZ2A0yw855f51/jGLTw7q/27VFeRYqcYG8LACZmjNHvJ2OgMnkTMZ2c8hKrYSnaNK/xk0lH5L2Xb xRb/saxzQ74Ej8jdGqPxGFrb9xe1vl5ww/Hyj5kbLFvfYtxg36qscmqSzWayTk0b2ALI5XOMTVtI BQ0qm2GZlENLDGiOydNYTE3an0ulaCymhnVlqiUSJ6iBG0Hrk/lc0BHUafyotUpQ15ba8FPpXNZu +KgpNv5Uzra3MDQFyLTqWFxqPgbChQOpjK8bxrYl5PPKfIUtMCfafXyIvCuZIXIT2zqwg0pj1qZR V92jHdkaHcXdj8XxYDwBuCFn8DZcls174zINfne+wHhtY/bVAJfnS2BH4LAzWRV2ngagIS6voO+5 2Vj8AmyEAc7m0yrgdI7J+nNJJu0FMpw01GfIPCTiGQW3SWFVzdmI/7fDD+czedJzqaTam2wehlF5 7I1GwnW7Ux8LossriP3tGczuNZVSf4ctVfBb5koVrokps1lGBZ0CUs4rU0LIVjzJ2CgaC+gPFX7z /vlvXlhAt65RNTa8MJyMF0A5glbdv34YTDWfifo5goGmJYHnSqhXZr+JQVHP0TD4FAzWODSMi/QI gMReTLg/l5wga97wgFHS2hizPxhz9aoCtXSrQDRGvWKduOUn3fmt1AGJ1nNxrO6FjAzTGEZLE0Ng DSpgU1SG0eEnYEoVqc2YG8jnAFdmw0xpgehtnklGcoDDCe8C1RIdO3LSupEbw5hrVR9WPNVSVLam roWl8G/MTPsuNeuryUR5QY4IBU+trTPQU/W4ADyhav8u5sIS2sMlEeyA4gX/R6FOPE3TriKKh0bP bx5JESv2Dyu7ul/5gPW9c99AykB5/m/vUW6vzauhIeRu0PBhPFp+yW1VHrJuiuvDh3Akw7kw4kdm uvipq/lS91h3OAEWP7AvGzBKCVoz3Gwkn1Y4nU9IL6HwFHgwD19CE298SY+J8dfaHc+opLcIcOF2 62yuiR7/eIZEC1wlzmc+2GEPGqDDAY/eboMWOjTYStBgUy1afIkgeBUo5SqylLvFpVxWsxalppKt T0mRWP4yfmClX3mQONeyXdexMwL1zbqY+YcdIKEmZnmt65bxuZ4MEIIFHfDBSWgcRuc+NRIIp8M3 08jtCU8b58iSSNZNdOR2W3MyCSjNYUr9mg8SiJjcZKJ4CAx0t2uu37qMrWDkpiDyELvg3HI4n0xM 6pCxkfg9XgzAFCn7onk3NL6hjEbgZp8mP51pTNwnjzU8VLcUuHbP5wMYjuKH1CUitN0gBuPllIN6 ifEEVRI0ePPF5/Q7ATYNfjT/+EgMkDIlm0S2zVEOjLG51Szqga9EHuxYZfhVVPgfC65wIDOcOSky Xcf4JnzicpIYSRAR8ygc4TKL8DW5veYfJXlnMZrC3JcZcacWI2Lg0qGN+obVVC8WgtzMYQpAGxm7 PK2KBmxu94+2I2fztq2+sM3YmqVAozGMsk3AMHOihsv5wrV3UktBQ+7QR6ktzp4wrBbIsZF/8Mdf FYCiIzhPAYQyw3dAM6KhgWb2jVxJJoGaY74LB2CGZqYpR62Qq9pZ1I14lFtodnVbCuIBDIMjkdjz j/HERchKkl2UxBSxoNVNh3nUEyEBV6NzC2DUg6lfwsMKB+rAlqpKBXaDobwbZFnL1sIoMRegmseZ w1WMDT/A7vw1F/4je6hsWi1kK8eJFxDWz4Qj88lt5KNMhrZtJULHtwLLtd1v5zGKww== xWT4x55VpDbDmdGjYWyzHE9Uvcp+fGCeJtzCnQ5yO4e+o+2Kn0EbyknqwlYijBgj4lzUXJLS2sIg eQew/BLmAMs9SbBp2w0ZCHiopOllkcNu7NJmKCji2LYJ1GPGQFdxaSZgUXxuSOFp0YATRId51OsT bruLrvESG5JbW2yPIVCCtG4QNNY2Ove2WDesVtHHbJkYTZxFntRmIXzMZ07yDjYTVwNlPSat5kgE A/3NOyjjoMVgDDVVxyYz/pPTnFo2jaAFK8CELUeuge3AdjNzhjVhIDROPU2znn8xIX5xI5hy5ggM 7LvQjzcDfTM4xAwN9a2yVnL+30VCF5uZpK2QglaCUZFHngarlp8WKr9VO3kXXJpsY+t20nmrc0uw rTmihGe8nM5Stmk4XwwdpApqIDrMOGowWtkrNKCBuFog9vrna7zklQVJFhprgOSskgCbUHTfT1Cr j9Vs6MBRUhvZC6Bwlcsmgt7hZjMlLMPaKEWt3IyI4RRTrcLibaPsb9YqGSafycTZhIXH2PDyQsCU QqtJAW2g+YX72q3aKK724fTPt4PqoDWcL78UG1BvapeU5pixrbpHTAe4X/N/zsYjo8fF1GzGLQyQ Sk2gMarByu3xv/wEvPXBDw3jbHHiUvE7N6sGPBDuwxeg3+X8N6BuHwizL+MRg7GNyH+iTHpTfzrc b/4SGIPjxYQvWfthOvcNeA1HB2wIUpK+AQh4jpJjoC2OcpyNfQHPV8v5BbCmLQG35kNO58pUHtam A34kucv0rAKfySmv+h0KPECx+9rxKwauLfDDsW4PUfun3MmhZyLwoNo1UR+2/lfOvrIcj+7sV32p pzADDqn9+aFwo8mZo2Vn6NMAINdK6QGwH8ozHwV/x3+BDqJSp9Js5tJVHi5GCDVaTL9noyf3A4qm opfx6MnXMgk/samjm0JSfXCjfkIPDpMn3WW5+pFvfJ/t3h5z1Q/6sag+ZaPHt5mvQPhkuhOITlLX vmAgWvz1FIi8fyQC0VWhE4hd9qqBOH3J0tTxYwQhTQcqkZuUyIqXoEvV79TJ9XsxWc4lc5mnzPTp KP5en2cfkvRIe0qf9fmKIBS5WWNy/2vgC5bfL29Kpdi8Hq09VHZ61Fnp6aJ0ljmp1Lsnqd4ptTwS wdvnU/rsvV1RkV5LXUbjoyN7OZqhH4XKR+MlULp+697Vj2qpX8roW6IvKAisyAWiT+HzQLTxUwyE R3QiEO+c3AfiuTgdiH396gbi5ccUHFp4zaH5gvLgTgIrMKrVJRjG8LqwPxsfNNLLy9PqU/2+AwZE 1wuv19V5/r0TL0lDG+0/VlWkC/BbY1LMn+39QrCZ2st3XZ3JEJh92LK4iBwt0NsyWbnbsvzp/fwE vZigxPQP+NRZmJqAboq5+qzLhvOPewA9M8OICvkAUOxF/Mwlkq3cKlpsBPY1SgCwuUby4XD3A3VU 7rxCakE4FJ+E18P2NU2lOhIpcaQN5iXV+2rFEFJf0IBWeP0sn9kizbC/qIAd0oHwRkUfrJD6gmLu qhzZvVtMWlZjFXffMmU7pGfFm+zs3hppKtKLHg6vLxFSeV6wse7U31K2SOl6+eLUBmlmd28mRI6t kEJOTj2+0fWPq44lgXcagaN95rzftUTaOGO7tuRln4rdd4TUF2QOSoOansAPwsuq2IJII+ZZDT8m nydMBCBNzU1z2qIV8rZDIQ2pL4jQptPTvsTzFkj7wuvXrGuD9JTLZOt7jCXSt5P3W4QUSksdWjSr e8nw4Ys10qPAq7j7xd9aI72pRIo/e9OWASnAAtFGDyeFotVY0azu/qyestZIU4/PdP3iqG2JdKc+ zQdTV9UbIGEsxkrX5+NzW6T7l9d8ww4pTzdudp8MSGU5BhbNAx38pu47AGl2YVw0oUY/KSN9jIcN SNM/351bCSkuvRDSpyLdauaTAAtAe2Aa69n3TzZVPklZIaVb0w/eFmnusvY2MCCFWGS0b/T15Lpj jfQi9HSRSMwFS6Sdy2TWFmmrkbpIoR3ZaqzPKbrb7ERskK6WnVbjOWuJ9J5ejg1IERYZbZe/or7s kDbp+7dQ0RppKx+6DweuTiyRPsTv98GqtBvrQyl8uGuHdEw/xY7frJFeNflfgeFBWEPqC2JoXwc7 l7ZIvwuT0LkN0pcT+u2tlLJGeh3d8QUXB2BNWo71PdkL2yLdeXw7oKyRHgUCglBvf0OkUYQUjAUT ENfsaXQndzQESAs/Rqm0Ymb3MtLv/IEB6U8/OxUQUjZUDJ/pd5o2mP3CfFmDaGMmqXTVpYLX48tb gPRUNI60drWgZaTLk6hBEAbpvb60aNjXZeEc7mK4gLiha7W7OkSaMCAVVu/BQIgPZx8B0vrKgDR6 TMUfJKQnzEXcgNQX3OmedyUBkTy5a7VwpOxyFmAryyFESptGep98+dWrHh0ApOcBI3kFoRZVtrf2 1KRdBNh880N7bnyaHDbjtk+jxeP5xOqpIvmL7X3B9m26djSKKU87pm25dXr2rDy9N4n31m23r65K q+ej96H908vA5NPhaWovoT01UYy+Xn3/sn+7c5/POzz9qpWtnsoUo7u382vbt4VljFU2tcajWTze ZX+Upy/GZUbff1ZWGsXMzx/22nsOTzMvYYenZ19V7amZYk/p56j926/f4Wv7p2/hVM/qqUKxt883 3vZtsL0Xi/ZPU/dxzv7pceLjzoFiTDmfStk/vSom5/ZPr38Khw4UK+wv5n3btwP70UpaedoXjE/3 LovfytOBaKJYgKWrU6vn0po9YltVh6eHt3X90wVuGaZit5IOc6saZ/s60+xy5mianR13gXFXKVPn D9Vd/rxTPYl2url4YH8FPjXawFAMVeq9l/rIFwT7wU4VvQhA7IYsDPxdanw8iAAW2KmB3eDkVic3 hR02dNyOy8bO/WMbG2lxNxlCZqSkjZ8VC5XnR01cU5e5WQgYxb0VMncAOT6OrJCC3aDA2CKl6/TB pW7fV9FK5k72NvJqg/TxxRYpUIwXSSukynpp7D7dWY0VIQ01B4lPBWljgiM9CkRwpKnOHk7edprV 7fuj/f1djMCh7L7Gpkkd0vRXJHzyPLFGmoq8WiFFthgaK4dvwXqkyHawQZrZhbbDuw3Sxz5Cqu77 +rHuNPYy9kih7WCDFCgWQB/hDEjhepHR3joQ+Ori3h4p1Ef0c7oHn8bUT8rsC6uDY8q5pdwuWaEJ 2tHvB4WSTsLYtUSKmiYvoE8phfmrdAs3ZPD2FPONXoUNndBNSJaktF5wl14xVothfyrxg4pq6gOp lNy7gb/daqsJEDUdiZbn4pXUB/CpCs3/GsKsWnyKaAIduGuDr/vQClwdKAgkBVpGgPWmvb9QmnRO cTcfEHr0eToY1P74gsVFeNSV9W0ER1u6oDno6OmP1ETnt0RdLlNffDUI/+yq1DmwctQBLPnGc5Xh 9kJniIRGyheLtaD8J3Y5d+1SXbTqEph9pVO7TOyOicE/z7jHRu+oREQ/CdcuNKJbkxz94XpVZJPL PiXDCNH4knuHFy238cE/bvMXAlYSwQzC9fmAW0QW44OKr+38+YKkM4jGR/O/+HsvxDqQZbI1MPH7 wQ0YEbPPmdqr2JD2/U056zDhTHefF8r3hTVXDpAwBmJ9VBLP6xLLIHpqL8UDJHqUfR98rhmEjzZ+ j7PxGBN0BIR+S0vhw7cT+5JSZqZdDVriTYfe9FchINkvYyrtwrar8q3Gvq7KFypvJF1XpeTLsxha 3Lgq1dnwMrSTws2lM6GR5I/so1VkR+WFusacRtW42Jdn38zsQIepvVTjmw8ImoI4n6uL0CBh9uGf W9tpoj+YnUc3DrQhC/IoyoTR9mnzLl0Oy2xzfEkpA5ccQpY0ZstP+XMNlOaHIQNmWHfcTiOq3/Lr VqtO9ih6XHcDduU8k9R4txBDf9BcQSzotMFCCnI7/R3bCVWnMyhNJ+bENvFGHWHRS0Ec2CnNL+8o Q8/AWJIRm35dslaDhOsFPKe+5tFjsxbmMCWSnqibkoZxSlRJi3QYa+Fjw9OjBnNQ/lW33pZsNEZ1 rzTM73du6bwxmahoM7ug628rReuz2ZhItaeGUU7rtyWfzLrYxmvfKX7Hrkunam8su6TzXaBOOah0 17fqmiWZP02hU/ZKo5h11Pnx+cu7KHRo6nxBshm8j2/CDPiODIG5qDweOOue0kDJcmwDYPQ2KcZs k2Ls9iiW3Ixi8rYsM1rMbLh+ntGjEFfThJB+F/OgHbPl3mhFqtDaybHlSYDYsLFelZ9nRkt8/VW5 PNkj6I2s88vUQae5ltRZOktVjDpWvYGzvzzZ35g6NM/17xxlMq5TWKqGYCx9apOOoL0SdoXcxLPt iP3C9QWJaWLQLb10RNYuYFeSxDRBWhG3s2xY7JpnyHVtYBXMFrOyDaMGJzcebhWuCmCJP1cwsr2K n0sXD4kBgWXoGKDOryYyrslNa7A8oPVqMZev4o/tHu+tS7KEcegUoQAAmoLLtozzmIsAeF2G99cc n8He/9VMntx3Lz0R3YbkX647spFrbXT5JjoQJBgfPBlxnUH6I/TT8+DPMNnkisUHuH/p0a3oQKyU gRmsfRdkxDItcYe90kQswxJnzkXDEk/u5RcrdyMN8y7Zekim5/olvoYvIblXCO8pdqVNf0iNinOj /m7nIcGdsrZD07tkvQ1NlvxgcKmwO6kd3RvTc+O2jPEYgYNDZnbmfKU3KYkHhHMy4J2fpJUh7cXv c44Ohg1ksdzF3AjzUQg/efA8Fn5sdEtIHYPHxk0U6DwNelWakuPHdMr04kKvTLsisFGlkyd30V2X 9eJOu8WFg69Ltw1qfku7jbBwEyLhCMdtUFkvJ3eFTdfL4kK/Ayb1ejKhVDq5CzJr8jnGyRemnW+t ARm3PBtfn7MAKNwE9LsdiQDQR0HLhMkQEMZdl73QNjoXTibSZeFhlT5640b6TV11FmevHtYdFMJR goH7nGVfBUxTyij7vO92kjYOgRVEd/Yi8LdCUMfLjWVyr0NwSGHgVFXn18+b3aZHzPESFMWM1KI7 1oJjsQKtoPiCbnDWP6nQoAAsnnc+hy7pzwdttAs7YHq3ODzmDRv0TfhbwnblqKeiZH4vCIz2vt1Y 25UQ2IHbRmg847MlZWcG58WGmHbH3I4S7X5ulmgwqnM7mgRcG/ZneLj16izRTEEVHiSa0QMPgbUI jBMSiQYetAMba0q9O1KJ5rz2wVxuQaKh2Te4xtaD4yzRVCuJAM4Wzl4RHL1E0x293GjnONa6gH7C 9Ba0hAU7FMKPDq21lAW+VN4jUbM637s3x1ytG/jQeFyQmtGSNm6pssIJdZGMpEIWyrHQj+WBqSet Xu2Xpcko6/zEYqb28rLrXZU2+MfQvOnDmtYRCvcGxV7nUfQIxyEEwgDF1g+D4JhM6rV60xdcTnid VHIjMAdHlmX8mONu+PJj3g3Bb457oY98NwRyjNrc4qsAQdJz3sBIvVkVQzSFPY8R7Q== htzOgGT5+IKOLPLgXb83yzuYNbCN3RDMvuNeSLqLATiE+r3zLgbhbK7fQyjmvVCz973thg+Oy9C4 FyqZj067YdxiN+x5CgJEe6XtbtgXHHZDPHTKZfTIfoE9GyTPbHqGk1JbkHYeiwpAOgi42MjEqxsA +yJYkEFF8juubgDse8+LT9+RYiRLnMS47AtWq9w+Ss1GrymEEw6ua5tgOrsoAtgph0Xqvrh02xKK UhuI5o1pIG7JSAMGJeMQO0oSuabvl60TEI7Fw/KCrPK4xWhbAMz99Ibs7Kb3CLEwF61tMPFAJPQn 25wN6OeSIgq+RaAUFcNkI8N4AntNX8cRRF1CHIFpFx4DX6WFKy8LOBGtrLVloe1iKF8u+/H8kVUu USm3asLbcZ80h845g07akTfPoXPOoEN3d2whh86MFM+gkym2cQ6dcwYdyhbcQg6dstasM+gUD/ym OXTOGXRKtuCmOXTWSJUMOutsQe85dM4ZdEq24KY5dM4ZdFju20Y5dM4ZdJIc2zyHziyi8Hhom/NK zzl0prgSXTgypJh9JtDxwt2Cxm02uzwgCUuDtFNOXarY5xP5FNUQE/D2GVPimvGrppNEk6fXnU42 2m9V2+vVWIV16dRxjjOTqORzT8Pbn+s3eos4s8u5cyqYdMZXRScL2+Enqzgsk/1CyAdzt+A+3fhQ xpBtp16c00SJu4TFj61LdKVLrp4rh07ZJc2pIFxT5gC7+oiyDmsvTdsUGRKvH7L43mqkwSBuQdGP 8QCZp9fdbQyG9kiQSoQNzSpX9K1mq7yThoLAVDfs4F+2xD0HPdU8hYI45CRu4qrS8tMcdX5ywpCY IT4S2wgCsw+4IbBpoNcaD8I6MCsRXN3NJieUyXXvZq/NdHJ1qxRT1aPoKcl0wP4QJjDGsNhRO9se EMvhLJvEcbbQ6ckw7MXkJvnOCWuqE6YTKzCunr2b0zkPTL9SG7ZK11p5fC4Rxh7y+PIu+S+QdcME XUKRjnYx8O7XUei6tGvbJTzHiiyhSe/B9JBaaJHHp/dgmtVB4vnTPJj2uqUHYM63IABQiJMJgTmn yDj1y3AqCoC5RNV7GaTqXt0GxRzCArxTzOUqBDeKGU4kl8UfY/ZMuffmHLvvosuqkn9ZXJEuduul 6ZQth91E4Qxix60P7R6D/rhmPpZ7P86rm9TYOzM4di3uutGMPWtV7MxdPBgBGCXMmfPlKPqZJk6U M+WMuM5QUXTIE9erNHZrH6a4ua19N3pamHD2dqUtOVxy5PTbWxSbF3POnts6P7DVI/VaZFyWYzo9 8lfTkBfrokfaZ/ro9AxHTnZJP3JJj8OkDnbnsFVOm/1+7lUfe10GCQJJCFZ803iUY6WPkdFpGQ15 kM4ylczxyTBzzJt7xz0zDsutJumUVZcIPDI+wgw0Tx4Zxww7bx4ZL0lxzp4rXaf0HpnkXv6b0ntk zm09MnY8Zpees1fY8ea2sJLJ0/MteWTAytkn8124e2TA0JgQwdCcI4im5xt7ZGASGr35fUrnBB4Z H1ka2oYeGXRafb7ynp5jQZg0UUS3e3rOuWnJkYWUqDuyIQ+10F4a81BP7oLGaBpSZVl3EwXQ5nY3 ZYYLK5eOPlKF2GpZXHi6N8xxRy7chDcfGlR3dWvfu88Qpo8RhC74CPLqNs4fvUBYyMNmbafJOVqP LHoQEoYohcTWb6mnTnaD5DpDoF5Yc4FqnNzrEBw+rJkPt8Z9fWvkw6H1Yh1Tt8V8ODT7pow4zyHV LvlwpBGqm+XDaRGqeEbc+hGq1vlwXjNS18uHs8kW3HI+nLu03EY+nJYzsnaqBkE+HPk9JJvkw1nN S2e27Xw44w3tcu7Qpsc6Sr6YfF/xhvlihIdD2Gm1nSYBk882jInEJP8dUUyka8aXlf5ucWLlpAZA IRQlioR0zkZHcNa81sIIRTWeHfPE3eEQKvFOmVwQjoPd7OEuUqQpweQ6e4eYx4hnpHkZFqGsj21p GdrFNBhvoHLNZVrrjNbKowiAbS00+R4twg21cUhtAjPaTRuHu3jM+zI0+foQnM2XIYJil/pBfneH BGc9W1qnwUI4m6j2RlDqBTN2dw+SXzETsrgSGKZ4tTBV2jJfjCyWqvHys5WMVGbH5RIVLxmpzA6R 5UiSkcrspKxAec1I5XZ4gqQbt4zUh61kpD5sKSP1YUsZqQ9byUh9sMhItb0G2s2lVTFfA60/FSUI MzIsQ4troGEu1p19UJ6XaNv1U+Esd7Gtp8LZz8s2U+GwTGESw33NVDgbim05FY7YrtwoFU6KiHC9 pn7DVDiLiIg1U+GcFEM8t9p0jfD6N8JDjRgTBaaTEe95dQQnNr4gUVQVBLZB4Qn9Lc0wf43kIkOi VLGsA8W8HC6gFDb7O4Hw27ScbueF+YcORzjEm4N8mxbslP2lF8Sbg7Z6Yc04jZ11MSTyHKACmeJn ID676Qdi92+1QLyUfAvEz/O1ADBgKvDTo1TOHPw5DUSHifNArHpbgX9gQc78njqd+yYfrPxJlwIm iEwQL7unz1BK7bCFvHXltqOdfS1DyZRhJ6zeE3GcY3RIo0fs540N0swuLKr9bJth9/jklOz2yynD 7uOqY4sUFtUe2mfYjZzqmZU7GFJDshssNa0iTZrr8f3sTdWxGpPdHm2RAvIe22fY0fU8fYVJS2Oy 297tlH2zyztzzLATU1ZI1Xp8sfd7q7FKuYR8OPtll0uYcELaCulsMf1YBfGuGLBFGjh9jXd1rMTn FfTok8znkcrTaGqYfZuWb6vpzBViZvfnrda7tm2HsMj5jjLnyVsnTDp6KRlUUcVLEzZfaVhfGask 6TRYdfsjvPYfOyNSpOpz1Tm8yechj6Ydqtu4nRyKfllZSc9VT/lGDl3SqcDuMVdeK8lZab/yXmmn /65RSc5qQ5Qr5blVkiOkk12IpMd4GFgX7cDW5LKI63Ou+7ZWETlrUOL3g16HWZcPDl0qqvgsR2jZ KZdaA05dwvd92CmXIgzkXdJ5jjdZL4eudVSULukyILaSTWfVQ3NG6qbZdFa5dBY1UzbMprNyePm2 nk1nNTRfcNvZdE7nldvLprOVllvNptvMa02aTWdlfFhx8mbZdFa5dIYo6C1k01nl0lnco7hhNp2V 3ezbejadVS6ddva6rWw6ZV/Ac+nUs9etZdNZ5dJhfpgtZdNZza7ktd5mNp3dqeh2s+msuuTD+7OV bDqr+bOpmLNBNp1x/kzRg1vJprMCJVX922Y2HekJ72bZdFa5dFujmKNO6JVi7tl0Hii2QTadVS4d utd6q9l0Vrl0dpXy1s+mswJgEQ21YTadjiw/hoo5W8ums9Lu1fz9rWXTGQFId9pvO5vOaobkmCs7 Plkjm84ql47QrvSQTWdFDIeT9zWz6awGZL7T3ks2nb5LadsuOWWk6g1A9lUcJPQGYJP06iY3KwnA ngU8CBxr3RGuynDNdbHj5HepV2enXWy3Xh153QT3enWEOWu1kCEOdm06OSsWFjfqOJRyI/ZTOMdb upeqI07v/DIuZodMYRc6uWoAhlvOHDplv5w9dQlKmFbqxbPI1FtEx0ujqxymVLmdV5K5wcjL3DnI ZK3Q3abxEueShNlKPKJDmTsP1bI2KHOnrReHQnfkaUo2Ze48xievWebOeEuAZaE7r243U5k7gkoT NmEKXsrcqXulU6G7qOnwyL3MHeG9cBdGv8FaOWtBw/6ydgBi8uQu65L86iNVui82icNXc6sLN5Et JD3aRB56irUGc75eUpExizOweTXRk7ugMQN2jay0CxQc5SmIzDYSEqYZEiTBkOUTSXUTQqaMIq7v wgxkGx1MDgSrbuPo9PZ0i9FQANj2oqHa003KuqrUNjrX18x8jHhL7sV4zADnYFNRgKBE3aQlIZwY QW8I6iRG7KuTkQabaXUSIyThZoSJtRHDvifVTehu7VZAAMpCv7PKryTJOOkSCjN9pQm7yD3QFZao Tg5mSJpVCGxVhiwuY4a5eAXn4z0S15+c/bTxrgK3N/sxe65gKH4TlZYlq2AofhPV6XKr4Cffe7xp 5iNZIoNLjaG7jQ93EZTt3BKAeuOgxGNanzucvu0t3C6xqlZ1Eg9pW/vbeyIDiquQpCW+DGsvFWcC EiYy4BXu1s+v9FLhTrVf7JbhVircKRlDdjXuvC1Duwp3njMf18onsqqUt/kyNFa426RSHrkt7Vwp z34ZeqtwJ1f/WRsYWYU793qvhIm13M6t/eUYxHLsYRM1x5z7trXE2gdzFYB1TJeXH9IYJ5fMx/jG ibUICqwAsnFiLYDjrAT5yOFscEmVKi0BnO3kt0uLxjFG0Xt+e18wL0Pwm34RWsX1ES1DMKpn22tl jElM1l44fEoKYcJAL4ckJu1+mL6wrVIAEJTebLegGOnV5gAYaRITCcUy27IrwVzekxupNoKrZ7vP Sli85bjCLnkL/YNr3zHHtdx7jBtzXI2hGa6KoW09voG4nXKPRbnu2xZzXMu9b8ugWUwfI89xNd6A 7Ho1Far9ZJPjWu4tnXNvSXUYVClvSzmuA9H2AEfNGiDIcYUV6TyXe7SLuoGd2ka5R01hL6Mzi5Zo QQRZ9YNpSoGDi0MGJenBtL5OINYfdQMH3VIGfmrLuX0X/TRN9b6z8sZzPP/WU0zxL+lzp8L2+XC5 NkXj9NSXuQvtzRf4RrebDOF5SeHB3u23de5fKuJYce7NPvOPrpcz1zrr1ZCaNkse9m2QPr45IG0E 0gakKOtZrcPWEB5VpMY6bLs/mdWLXWqaQz5c7uZUsSwUVsJT06KHk7srG6Tpr4PTh4OFXRKeMfNP yhlRCfxJ2yKl669nlgmHUpm7b+p+YIeU8wWdCt3RBVukgvh5vmuLNPCym7nTkIKx6Agcc8r9a+4b ZhUuzThCjz4pKZirkWn2rVte7/IkEHeujwME7XxBYdX/DmLbJBy1KWpBWbjg7VjYsHU6mU/Xt1j+ PlngZHt/ajgNMvlON6hitvAYMmTO/pF1fu1ytc1iOdv7ljHu+M0tpKlNrjdTE1dmae+7FGsgLnp1 UGoHiCMhHekUcglA85CV5h5aRZyVFt2Yn1RQ2CGTW0yvW4obWZSWj6BTCefxEXRJzuL0FKfl2CVL L/E668UpSuv6zq7ShEFcPcZmRnG1qY9ZtV4fY/ap0eRV2myks/faT2817+fWdhLmMb6z+dBUPX8D /9hjbEHq13Lwj8H8NBK72TUH8HHhcgcRSVojwSW0PhLCEOaL2bu0ME5eOMRpkZbkVnNm9XfFqTXs tnENNIDds7ySZw0bue7dGWzr54cJd/ZXAntzBNQt/Pxebx7S+1SihgAClE9j9POvm90GEwHtq/QS 3RGBxfkavZVkiWSWkSoNo29mg7QoLFuQ5J4Dh+zE5cm53aZGoI3rO6WT997K6um9o9/5va2lcs6C +tO3DVIB3YteIVCSLeYOzKWusUu/sIzUhsmFutEgjeeVGwFzy+XxRDGXk0tvFHM5uQ== 9DJIfmlPMVO6sL0x66GiHr6/eM8CdFbO7Val1yxA0hxAvTbuNQvQ8eSZyJ9MkgVImgPoXoHdKQuQ NAfQJi+JMAuQNAfQ7p5esixAUnpa7pXEWYCkOYAkNrJ9FiBpDqDb6ZtzFqDcG/OoDEX55BjFv1yU z52TXbK2iIryud5EsZWifLKE+ctF+Yz1kv5OUT4bG3nLRfk8eeHWLspnvkvtbxTl0+dZ/K2ifNaa EimdnHRnqTeud0N5quvn8W6oNev6OVf1W/9uKH1dP3v/CcndUKR1/ZyHtoW7oVBdv83vhiKp60dw N9QW6vo5V/Xzkl/pVNfPOWbFKidxnbp+lgq7WtXPWMVs3bp+OO3MVf3Wy+TyGq3okMm1SSKSfmjh zetXXhAEbrj6LQnr+rlVANlOXT/neH3SCFW3un7E+ZUb1fXTrwdjVT9rTvZe108ZlXVVP0d9zENd P+eZtM1K81jXzzZ0ClX1I/Hzk5QHcK7qRxwF7VLXz0s9vk1z3u2q+q1Xj8/rlmdXj2/9FYhDUVz4 jidWHur6uUvLbdT1c05PkT3wbllirnX9nIMKdBJmg7p+ZlLiVf2cTxLJ6/qZA67xqn52GUNe6/o5 q4PuWWnbSO+UckU3r+uH9cviNgHva9+6rp+zGmBdj2/zvAdeV9Vvw3p8W6hjxXuo6+cMBav5uGne g0NVP8RjW6jrF3Ws6ucLeluG692ubJGVtq0sa6yqH7Ecc6nrt6E2TljXz00b305dP+eqfl7r8a2X g22qx7f5MjRX9WPtMlO81vWzdqZ5uVGHpK6fs0GNbm/YQl0/xywwxs16JU6Gd6zqh1cu3qSun7MR as6tXq+un3NVv03q8ZF7s5zr8W2eDP8gZ6RuA45bMrwaqbJhXT+iu9M3ruvn7Ncy3EKzdl0/C1Ji Vf2sdrF16vo5D1KKVdi8rp+z2W5alWvW9bOkGFkkpIe6fsR25UZ1/QijBzes6+dc1U/DslldP2xi Lar64bfNb1LXz7AHGBJife7GLlFdP+cTG5xiW3IgW1T120CH0dX1cz5ccLsdiLSun3NVP/neHqJ4 S6JSg5YcIZ+Jr1H01XwFcQX89mnpVpRzeKWl63aJaYS2cO0+O51hyoH3FnUSzYmLYAXWDS6tCu7D eg9OdMseqmxqDDEUzBiPRTDCFNPtuTbJBlsU5r6d5eKB/VXtofwQAL91FnKTPl8RhGO2XLx7fQwH grNsKhAq0HVfMHAw79wE2ELnMno4KZSjxWPhNHp38RWia1eLJF3P107pevmiRjdiq1u6lS0/063n pyF9eSAm6M5hKE13+idl+u7XYETfh2Zf9H2L+aHvF+d79MPJoEq/Xn9fgNl/XSZ6dL8Zn9HvB7dB +v3oLSIIV/GQIJZeM4I4328Kq8LyWdxdlD8SyVZuJWd2fs7bxUwocHlXDrLZMBfi27v3T93i3kyg 6vtsqn8Veu8Ucjvd8yGMVOnW26HizRGfiaqpgKEz/qUWz7b2f4EpidZh2ls8IIxfqeD1+PIWqfsW yx7PLo2MJ/lAdJK6QSUgtXmB9SRTkcfo0VG8YEksRA4w3H36/TJ84zzS6OEwBd6lT4p0vfsA5oVu 7M7bgph7GKFcUjU5tBs9puKoGuWOlJNYq/2iBPFlfgh/2zUo7NIq0ZZP8XgRxP1jkjoh+1tbefyw yoISB6/1FayN2ZPKZ8YuH3qBcJzbgSm25/DPISyp2Q7Eqf03SLYirLX5AngsOkzkYfewm8gkbYZf nubQXJWm85ZYunh4eItWY8FVPXzWbAL7c/pS70eeL8CKfkxDjWMPShhgbr/vxiXLqZh+EeFXSrWR 02ch9VMY1vCbQG8QLKtzdiDl/YL9Oga/xuSvlUQCfk2or1HR2n3vDPbmJXlyvyhXxhzF0FQxFfYF 1Y6+0qNwuKA8KhxoD5jaW+FIeXAa0x6A7a1VVB7UE9iD19XbqfKgReNY8A40ChE41giOuXEa1WiH Y27U49oDpE+D31qUtC9QjWsaxSimo8m9/HQJfrhjIewDIFeWeRlEuxKFTWLgT3YGvjbjijRZSalL 4LdWAjVBZWzA11saSmwG/BnBrz0W+WF2D5In3VlCmsHIXiKCzEKaemyiuQRYKsyhjPTxOoGwJMu5 ZO6Qf4t8VL4y9evyJLebwxgSTSwUqAiUhfWqSH4A8ZbyDtEKnmy/AIh3tAYxc3dcqJTu9g/fK1/Z i0WpW5o9oNXElp8P3iT+jQx749PDVkAA7NVNquz1js/uoCWxCph98IgDSzMxBb/eJiCJYjCNJyJ9 4nbu4+gTIHrnQPpUfkqewcX+CFjpqIk+yRM7+Eyj9YL2HJr6vktAvweDZj8XQo8A7FJY+sTtVY7l /nxzrMpAA4Dg7kR58Jmq19hLuHCf0upYBsmTuzq0jd7Bg8xTvEpxR2BeCp+z0F39qJb6ZVj7cLu9 kX100h/Z9adoKa0jnBeXzxTsIeS20oH0qfZyHkWfwFiwfi8/k+hXtvwYrRn6k3mank2qH0Gxe3p0 0kuVLno0EJnp1zSQJjdhxJ/J/XFwvzb8/skbtm99zRR5A1d4jPvJqQrKlc43hcoOL/cDkaOrFJCM oXsoKKuBvWruSJWbJ/DBeSD2s7gG0hI8OoGCdAQkbO8scPCzK5ivLqAgxXbDisy6nMkL+5o/kJaZ yhuIseEd8jCtOk0jADCK4KHGIeaERlVClpYwwxlIy5heWlJsNf4cpan0cUyZ+LM40oXAb5UEVI16 sjhuXERkcztdp/Q3UWiu3XSTNs0+egAkLLwBJWEQrWikQLaNnlGHmVgrCtCnL+LyWJjY5zFVPT+a 0wa5CqPUJuXJzqzOxPeaX8oKvIqgyZEUtUZrJyGPD8hSOLuXkPmygL1O50iMQolGo8yU2x9JhqYH F1DjupKIyZxlWhpsaYaYwVswblAR9R7/fZ1W9yLierI5GHb6BiBenyRL424TMMwqxzSY+iEzvD3K wsV+J4M9fuyAeXlKstWbSpyJBw8uUFI9fd4bhJLlfOQJzNBrWjp9C9Hng+NDpvH2WbEMAS6m+0tn VbNSTtAsUDUfr0qxBX1aGt5c1asn0fR5KTY/jfiC9e5J9rF0lnm/Kr9fPlTytdwwVhPeCm+HT61Z sTG5772UztLP9CklLr6Qtoql84M5D0F+iiL9QL7WoN6Palotkr6+YGZ3UamUv0Ozl2oiGxIP+bzw XeqsAl/Zn7PbVo3jQona02jnC+kwmG4ZnL9WDBaRLVJki+FoM7uF1u1pocaPy9/h8E3trD1mTn9K VKnanI7FenXClBUVsToGE3+7hMXHryS9rbjaD1hhRraY24APL/aqL9VG4/i71K0mfzwNF8KjoLRU 7DdNmKHTG+V6CAqKj3YCyQM2VNypKmJ0V6xFx09fpe79g+CMGd13YcTNApnMNNfC/MBWE4mjh3p/ +cqcHp5/3yKS+4LERD85LO6TTvfWeOzgUzRF7MgCnA1Jd3zI93lcziR9LC6tZDqyl6NpsTorX7dP X+vVdPq91D38Fa42nzPnAHN4B2xg9YS6Fn/QnopWZfGuf1BDM201z3LVvzXp7UrtZSiROitN0b09 nRTp0NccOKrzbjn0bTKaL+hp6PBm0Tzmcyim7380r62tGAVYrAXpHV1dcV8PSIyefnQXhzXhdXCd ngze9sCD9vUpJSz3yu9XbKee300X6/m921Hl9Xz37HD1WYyVEynhHtgdBw11f/kLi92w1CGP2bAf Gea9PSBaf14KyUq1X+pW3l6sZgD5+qwWO7zwZmuyzRcklKsbsNzeHpBj7gNWlclQfBbPAVslOKsK wknhhnTMqMbQ2pMMhNlij2CteeKxNcWMeIX2l83EOsEebstjDrs4EWbdduIL/hWlxWIX20BpISS0 tPZdBuyd0UyRXVucZNt1tQUeI9DWgOQnlCvIrMc9fBY+ulj1loXW5FUg+hQ+hX7LOrwG7xx64Z7C Iei+e4X+OPD8ZucwEM/FrwOhxd0eMj6hLQo+sfUOtD+LmBEaEYRYIBZ4D0FL9B4zYiQ3Xvs4Co2P oHKXGvR+qzbrYfKkuzytjOv7wul9qPdzOj8THuv92Nlu6frzqAUIk9qrftyIt8hNLQZeQ1V5Do6f dpF+kCwJgarxlMeI2xZzjXuvfZ/Ofqh3gP72kVSPglZScB7Tk5oU6U31Y3+xC+X5AKAf9sl1GIB0 JuiViM21J1/Qi+K47lYG9xeyvdtGeyqHCKiNdMu16U065r+kKRlkmy+4DZXVjeTAEt+K/uC8fQMd xmUDt8TsUb5uYImzy33cNENuNRu6k1pJXpjdjN5U63mLuwpuiQcO3iYLdaGFTURHvinuhzIKHJ0H MxOIXD3l4dZxCv+U4TZxJX09CO0eASxgB2nBracFt5EL+CgBt5sO/FqH/s8CPDei/87+sq4AUMQt bqwqERFbNlet9hcTbq+Y7/nT+4vjJliB3UDtPXP9ZdhYgeS33Vr/m/eXjXc2sCrdB6wNF0qYtndn jC+46SSDXeV+r+roF/DMY+ywf3B6+PLVryZu34XKx/FsQKBC+YK2StQWtRkg+b0srzW5De5iHpbX mpiV833C5bXm4oI8tl1pYrW4vMuxdRYXGItnX6f3MctZNqTLa83FBeSYl+VlubjgWSFb7n0ZnQNa JA5clSef2cJr+zJfOstkTsGfo3L5/Wr3Cn3N13IrtpFeMZ3aQ7nTOqWWJxels/RdovpUv++Ar3S9 sD+vFqq7owxt6/rzBQ3Ov7/iloFj2a633Uqh++/y8697uIJ4n1DIbtlGttGi5fXyVzRKzYiRrNet +N0dbChfcE1XpCeOh2t/nRMPsz69jn9sDc+cA2Zy/5jHidcZEv/NPlhX+032j33nD9b0j4WEQPw8 35NMEmCcZDexVaxWOYy76C5L9f735KBemnC/CJY4+oSCF4XVeyurBpxQtnyOThJtOT0UrowDzxFS 2aaFGsYjQqWwtoTJnNwevJS6d7/eiLgbfar3A2h/OYyt76IgGi5+Wo0N+GC/ebguY1sMF1pJrgOG QZ6DTYbrC25nfr36YdabX+fZ1Wpz/AV2VmcXz3v9e+wsSf7N59d5uLI2vvH8Og/XXR8jm18Cf/IW 5lf1cLG6c3k5+F+TY+0KFqOI9zY6w40KdJsLduE3POSWX4viOQxITlvkvSrxpoZyIlKIPvVL02to fidNaajQb8HUVfVGMT6EKN5N2bI4OulgIJovsYQexJesLslq852u8A/aZ8VdbJ/df2LPsdFL0pKu HV1rIG7MIFY6EGf7Z3iwZKojVbBBwczRYuyKhSVxYUThWRR+SqDfkJ+/SKm/0uBTB+yly7CAwjNp Opx4Muy+UvWf4FHgHZWQARvmMYv0crXq0guYsFQDPGAS+qzn9/BUYd0IrEuUD0iB+UeH01t14T5K QfbmCkTKdKJ5KUcuokoCwtlrYufXHRoL2sATMHKxPUf9iYRPnicYK8G6wBLFktnrbw== OeSfXTEaT0cPh9eXMMhzR+kNVrPpQM4YkojwLCQHChEKjEaESOVp9KYQIaGrJvWe+lFJ8IaTgP28 UUnwJGl9u1p/cCKgW4VtiCCTgDu60kiQfJ4wOY0EUrqPxGMyWjnv4ZWQCAmN93uBOVWTSCCUH5+t +ADWGFI4QSHC6Uph7FVAI0IgJT7vq0ToOfABvP9GoeILAiDLZD0rOYLozAwgCADoK39JF714BGG+ osK0HuC8kK4IqcjuOn1QPVdSgdBNhoESKq2XNbYjOw6DX27SBxTV+bUpU00CzgCQnuwIon0/I1jd Dmu7/ThH52KbgHhZbCph2n0bIUXKEe2BxFISxWxBPDmB4EXX6TzYQwCUtX9S+ZnrQHxtxFQAwPdK AyBRzDOIecCdlNjKAGMxgRB2FBCPUw0EfXb5ONTpTC+qOHrEhquvqAfb9RckPOY0qscBidTR85gR BC9sxuePX6LKY2uu+MdvYgZReMwEYrbacBgCJnVwHvMwjNWOpz5AHjP04ml31221seKLBiIQuv/q 4AAGA6PUUXdkUkoM+B/vfdDvyIOvDZlq8C1acYRxR3aajcFsSSq4DGJL3ZEHP6v1BBc0uWCOEVQR PwrhPOaUCz8fpKAXrqdEEcQue9eSXodSjdSUUFgXjVKtiFtLD194RH0GIuPvEUyk6kEPXgXGIpxL sW7Rp9CxlJF6HoiuCg3k/JMC4uK5WAv2e88+DRZP/YUGruzXSyppWMCmkdKw6v2IlGWzB/TMc5S4 F1UaWaUfiS22ehpgaapRiUmWKIobl2xSebhhva2p1ubw0qk1u4T8ydadkr4qKcQFL7SLInimqBum wZzmmNhbNoGn9fW+Y+DBbRF0rxeHxnyc+voIHrK1w2k6eXK3k5AySWsvfFnxlUTOczf5XKNeuqk8 Vy+agQ4bOj4+gzK5eDyonkQ73epJePTEnqTPXvAjOskUBOyl5LThf7RUqWK6S2OHiAy1Kx5F7w6F TPEuBbTxUvZ1FEYUZSNPnYBks1KPz1pWpWX6p2vy52UMTmISv1EH3ZYmcYcyEWktyQDme8bkPE2Y 76h3TJiyw+VMNeypvjaHcsubHUsmlesMWmlkDOGWP8xPw45d2zuPGh9oVZjR5LExmkonUILqPs5U LJsF7JytspETkWYjzfwFNd5NHCX3q9y7jKX3HUcQdfDuc5BpHnTn++z7vCFnLoNH+IODixLMfIzQ /CBVZM4SSXgN3lksesKsMvRHP9OS/UfSNXgCTBI+PmXfj2oZ+e70ZHCUbCTL1PhIOpVQqIwO+m5l YPhNZFI2upYiLnEOzOvVvHDZX6GzonoHzw5YL1r3TiIUw74nLy5hYVMqWapd3coXuMFDimL76QD+ AZPTfgX0bj9QsPTdD3N2cptmzvZOWaZR/gEr7C6cYAaf0QQzPGkm0VdfEEkEdK6d3DusnSf3a2cN atx4a8IHNDNs0mXQh0wLDGOQoz8qvVM2kplWYZ5inol+Fw5Bk5M8pMMLuhadGcanx2zt6OEK8HmR YfvTQMkXZN9rN5dgftMZ+E4huS+85sH8Hl1QX/PEMfte/TWQdhA1OR86DkMY5al09kCjO0onxaUT YGxsR0YTAV0U8L6AxlOErZ4sSjAwAC6kUkQH9jgmg82ND/XXZ6GJ2NcEk5In7sgdnnhDTvM18wag mCN34Kw72aeT5f2HKyBIHmkzb7xDz+sQ/nmn4R9W/SrljEjP0a9JpWjLi2iVlsqGP6cX9Pn3Gwu4 5KEDuOSuAbNPE2xkb3rCvgfK19Kli5LzTlnMYCzKcr6kxoNpnRmeXRfAO5/Hyf3AUQsIeKZAny+b Jcho8nUq/C9+KkvVdCpCXXZ+ksn9o4traRKxkYLFJe8vmiySfLQqY1g/UMI5AMSXkuQlRlWmi42H sDQv2mUV6tULPpSFPZN7BmQR2z8bxeQdC2Zmw1RslKGOZlXdu0JKnjT4BK82QqNCX+VU5HQBpbuH UCIyxJI+jUs/vIo8ukghlNw7OnqXsro/3k4/laTkC7yjMXr2rj44wB9UggP1QQw98AXlR3fMSH2U wN/5PP5QH9DYA0O+NcqJBtKCU3+Lao2hhHlLDNVHmMLHNBYFeFHPFaWqKjRytcKka+jaxfKtVdg3 UanJYMHAjeAmjmUN7LGhYhheU3AjnTYww0wFwrmhYWkUAfId+iqDHT49M8plFfUo4LHvJNz3ZWEd yRRUsnQTChZpB5l0grVYPvJ2ekjf7+m0C+ns49ZOp6DwfcgGChadbgvHXjch0UwgI4HZl26vWI2+ lWE+xLTJYatnx9Df+iBxMlt9ajISi1eH1/J9LdXJHSt/Wj2/ScFRtQjXlz+xn2kkLR/SEoj+0ymE +AT+DNg525+0aOnt/upWhv0e6amc9cRivXk/HP1SH6Swiynwsbw/BCqarC1PEp9guxx+tJB+qOlM tFJNvqJesLiP3Z+n3vOUDK6avIL0Fd1CA9f0PnuXkm+TOHxOy5+qnHoHyGtSbnc/LRl7c13pvtar k51h6bb7EqoN4qfoOpEjKDcopTILtVxkpLsYJJWn3k9v8XoIdDmETLG/dz0E2h99ys0Qf+t6CHQ5 hC/4l6+HUGWy9+shSv9V9OXoPOPPsclUIpuhaZplkhk26aduVxNeuBbGn+OZP+Y79FGlJsPczUbz usDzXf7fZXU+XE352dJf8FOlTqXZzKWr/HA+4v0xtKzes6oiEZc5RdXSbQw1xIrl6ke+8X22e3vM VT/ox6LpTqzk2TGMormFpnTx+0jKDYh9jcGj948EtKw70IivBuL0JQv1fsubobHz5afM9Oko/l6f Zx+S9ChqDpgEJlsptrg6P73Ii8Xc2dFDoj5/St3XhJcnuvpUf+zWj0vHQ3RVkfu9awvVUsjamTkO F7dQgVjk9FS6syV6s3MluQ8sr21R74VRQlGjilsAu/Ko3u8r/NGeK0uoswCc+1mUTG5pB/reka5Q km72ARoUhb7CFRqWP/3i0U1XEVkQwUuToXV1FpW/FsJxeXmir62UDOLjrrBUdKkmjV1yhV3BU8xG sEuuYP9hqIn06DiKPcKs9mIljl1zhV0iVGxS+EI8/CwpD64Z7d4q1S3QOD7ArrnCaNeoxLAHGOZG MwGF+AGQGC9Ib4qAhfprBR7cMugrULwC4Gv79AC7dqmPLoIEv9aRQnWg+BOq3zBUAZ5UtnJAobwG U9u+pqSrr2B1UPD1jpFuupKuXWo/J1VtARB/92gX+SfQlWvQtH9saYR513kt5KuKXC9O2jdKTvXi pDy64mNW2SJEXQyK7FcBG8RpiO9Wm6PjgHIxVo9R+LeLb82RSX9XUTO4FObnwNhrcC3daiXfNja4 o5SrvahBj2YGrWYEfALqmLSTDd7YYr7JgrkacEnl0yiFQMhT+30bl66+gpeOgq895faz72da+fTG YLM/wG9o+x4lsfuv3gLJvqxBXP4E5bF8TzOebhbzSfdhY3+Md5Ute9r+NJRZZflGQ5dYGHziGOXT SFPWhvLNRMtfKVk5xPuTXt7XDyLFw+x9fOey/n4ZzEuKy35fBLZXI5qG6kjG4B4yhMhgATKqo09f 6JDwtkCwTYRlubkqtKFAPQOy9KSr3Rao3hW4Z071laYM7CWSBFVuLTtQtJzOQm4CTC3w9VEANE5B YoWhAtNfqtpJSPJCA2kZVaUl1G0wafk4T8jG1mngVbaoKokYuqwa3bFGjXvLhKQXjmOFKLppEblH rO5RBzbv1YVp9tHNTQBLVjAJV7QEgFRVunwRk5WZOwaO5QKYQ9n7s8r7d2mkk6rw8kBF/7hgcDuq /JMBk/N5DZWQA3V8Ecm0lZhP8j3vQgdIf0eSoEhuAp3rl6QmncXrMJTkCl5Kr8E+O7mFcu7mgOj2 SdnavpE8hNZOYlkwaS5BOfopetypjZTop+G+IfpJEI4uHrT4D7bSHaQM4VO7P5nVpQLgPagPAYIg VoP2j3P0UyBw/KhEeFiFT6Ue8aSz/fS8rjtAkeJ7ms8aiI4EQvXcSjMtsUC9H2Ij03IWau5heFcX DZWWiPwb93Mg//a9E4V6KDSmFLtnpKM81D7gqOVgIPl21IPThwOOIDRJMod0gRNWcTmTuyu7uJyw p7gcFJWjL3nznpi7Hl05n32BHUImwWlSI4EvKMWLyURIURoRYH++seAkdFG9RISq2FFJ8IKTYPV8 rZKgp5FAkmMxAiIkT2/CYZkI3Mm1jgQFywNA7ejNNQjkhDkX3eKznPgA2ga0kvC1VpBaSIo4xU4+ bQK8JDeaNQiMG9eJEQshD+FGYWYhLVhPJr/TepDmxQQC1R/ZYBg4QwIAdqvSEQSQ7XHSYSAAKAxA B0KN2VtzGFItYT1LSYETxEyF+NI7V2I6TBjnS6+rWwKAcaUOgJIm4w5C48t1JUwY50scBOlshHGu NANQQ03wXhhBaHxpPxsnhe+ZAuDAwFJheLSh8eU6TBUm4Eo51MQWhMaXDqR02vJwaUmfVTsDBcTj TN8yojEfXe+W1d4+vhrbkfGYw6giOI95pazEYxE7HiNdKhGNx6wYROUxp2EYZJ9nBonoeWytYWg8 ZsvnLjwWseMx4j4Q7ciBUPXlRgbBim96EAekkg/bkXtGECpfrtkH/Y68DiUOcK505QjLHfnAmS/d BdfB+juycqJJ6Y5/pXSML5iV+ATjl56geQxM5utIDFnx0CYdwYt3JO8hvMNeuuG/lTHlJW541T7y J8uX7f+9q/Y1j2Iq/Peu2tewtDBf57av2lcupYeX7f+9q/aBHFMv26f/2lX78uXntlfjb+eqfZ8F xO1ftY88iqTRVmtftQ+xKJft/72r9lGKHKl/d+2r9lH6knzZ/l+7ar+MsMjedjkvkTiAEd2xG0tA SRXG5JQqXGQvW5oJS9csQzXoeIEihqQQC26nk5KPQgrhH+Uo5DSOMhThQclTtBi7FxTnXVaW2B93 hWerelKwMOjb6YtF8GCFiYW+oJS/iOBxFPkl9DxeRNUuv4IuNRfoBAUdcMLF/i154WJvWenMGcnk C1rzBRpEmHZcCaiTk87PYUxXTvUEym7FxmcK+oGvEvKJ5d6pcp8+KhQinZdghzSaCJNzI29S8/8q +g59QXhC2a/NRvjppC8YBL90+OVqARuk+2X+czxrcX94wcf4pf9o8B/8m837GTbnZ9Np8CUNf20N fGHU1s9E/K2Zj/aXar5gnyoJy+p4uBzPZ5zwx1+AP/UuW3fNqr/gl17ogxcO/WHQJboPWoNHEXgu 2gfd7EMw4P+9f+AH3rfy3bnC7P+brPSX4+WEB59qfWvYsP0VPIBFLxuAgRf+nU5m4HGcWy6F8WC1 5EX5vZIgcBrK/3kQWKvh13gyEviZ1Cbpp5qzpfYU/ln+WfDS03BJFPmln8lH/NTdbAzPojsAx+xT /8JvbrJS3thdAl4Bza3azbip3OxQ/mvTK8axV9bA8U6geXXu839bXzr3jX73ayzWJg== PFw+BKQxvyL3ozyfT6SnFYHnlvyo/Kc5XcyFJS9gayHvD0f8vQcpvgCuXMABtJ+CUQYw2gA0RN8A wuZsxP8rfe8s58If5Tvrp+B7pdlyzE3GnAh7CyMWfLS6unt/wJdz8OEX+OEfP0P7L/3Pr7R/BJfh rQ81Gfkycldov/STJBfgf72STxIRrASMyecTmTyMlkilmBSd8bMJJpXJZMEPyXQ+n0n7p750An4H /8tm2Hwyn/Zn6ESazmQyuSybydBsxt/ypRI0AwBk2RyTSWWySX+GSdC5dDqbzoI3UiyAm8tmwQea yeXydDLnz7CJDJNi03QO/AKewRYIC5Ons8lULuPPpBJJgCWTTyYzCEbFZ2qTSyayOdiVfDKTYug8 6ErHWgZlZX6C09j54hZ8V2UmWZRdG2nFAXwpaehsLsMAkvhzGalPuQzLZPK5FCBPMpFLgqEnU7Bb LKCGqU0qkU8hKOksy9Ip0CKdYDNg4EweEotmLVoAqHkII51P0rkc6x/6zG3YRDrJpsF/LAPmg/Wb e8IkUiyEkgMDgJNpHo+xxdDHJBg6nUtnMmnQM4DZ1IQ2Y6atOkybx2mCbSSVO8GHvg/rCWZcJrhV lvZNsIuijS0eB1tqm/vkuwI3noBd9FPkfvN+bjabL8EiX4An/k+BF8EK5f3i1/wf+At4RWkO9uPr uu//A8wDrAs= Focus on evolvingstandards like CBTC,ERTMS and PTC Strong experience in mainline and mass transit Capabilities in RemoteSense Survey Services Leveraging state-of-the-art technologies with own equipment Integrated solution with our GIS capabilities Ranked as a market leader inR&D services for rail by Zinnov Experienced mobility solutionspartner for life cycle support Focus on emergingtechnologies such as IoT

How We Partner

Designing Tomorrow Together is how we partner with our clients to deliver mobility solutions for today and tomorrow. Cyient offers a unique suite of full-scope services and solutions across the Design-Build-Maintain phases of rail assets and projects:

Design

HWP-Design

Our Design solutions include rolling stock project and product engineering such as platform-based development/ modularization, train control management systems, physical installation and integration, and signaling application engineering.

Build

HWP-Build

The Build offerings comprise product localization, life extension support, and electronics manufacturing including our CE-certified product CyceroTM, a cab alarm unit.

Maintain

HWP-Maintain

Cyient’s Maintain offerings focus on enhancing the efficiency and availability of assets through data-analytics-led solutions (Internet of Trains), augmented and virtual reality, and cyber security solutions.

Our Solutions

Our unique design-build-maintain strategy enables us to deliver end-to-end solutions across the railway industry, building on the three key themes of digitalization, safety and security and standardization and efficiency.

We collaborate with clients to provide dynamic and technology-driven solutions that are tailored to enhance efficiencies, increase reliability, and improve safety across rolling stock, signaling, rail infrastructure and operations. Our deep domain expertise and wide global presence are complemented by our agile and innovation-driven approach to developing intelligent digital rail solutions as the rail industry moves toward Mobility 4.0.

 

IoT solution to build safer, smarter and more efficient rail of the future

IoT Solutions to Build Safer, Smarter and More Efficient Future-Ready Rail

Make intelligent, real-time business decisions with our IoT solutions optimizing rail asset efficiency and availability while ensuring worker and passenger safety.

Learn More

L1-IG1-2-ARVR

Reimagine Operations with Enhanced Reality

Optimize resource utilization, enhance visualization and streamline cost across the design – build-maintain cycle with our augmented and virtual reality solutions.

Learn More

L1-IG1-3-Cycero

Enhance Safety in Rail with CyceroTM

Get your one-stop cab event response device for a safer train journey.

Learn More

 

Rail-L1-IG1-4-Cylus

Cyber Security Solutions for Safer Railways

Leverage cyber security solutions for safer and more secure rail products, systems and networks.

Learn More

Assisted-Inspection

Image Assisted Inspection for Enhanced Efficiency

Optimize infrastructure and rolling stock inspection with our image-assisted inspection and analytics capabilities.

Learn More

 

IoT Solutions to Build Safer, Smarter and More Efficient Future-Ready Rail

Reimagine Operations with Enhanced Reality

Enhance Safety in Rail with CyceroTM

Cyber Security Solutions for Safer Railways

Image Assisted Inspection for Enhanced Efficiency

 

Get in Touch