i{F. 節t,Ryiqd8 7fD $H@Iy}%EjUk?+bͳg3.i8ک\~];U[nl)oh)!z7$]k7O9+Uq*Wnug\l/r$A]OҮ_V[ l(/GK!{#X&vB\_W9)okyj]SS5qW] oWsAZ䞼AZO~)< 7}T>x,.M™Ym\ӸT3JǺtLi%Nʶb/>W]Ǯ0WY$נJqX|Om~ϟ^>Tx4_ހr } ~s]eVhև#[m7A|?}>4|xy~zz^ZoJzZ|B3'o_Z7^퓗?ek|!l_'gM+yjI7hnj |v6`ΣwEQ&׋G7MƯiDBijJbYz^ɫgfykPݽv0uwW'|I‘vvl6 >_}u<-|iZ_2~5,ÿq#|xEXo[}ۛij?_5>Y_im%ׯe/X؏k_^o˛@ͼ7?py7oDϟ?uQW=X[ԛoσAQ6V)7)e;I@OA' nod)?"ap,p#:(\צO|J9ѓpa_/߿]۠l2h)wt__/Q\U7Vzp_ȕu34+(`~~ N3pK~ hokMY΍io_o?DdDzۘ.nO(TUDPמh]›|HoOC~>wխԋ]SU&W W,mG {'_1}ѧݾoP[Ho_K3z|]wg~KV6rr\Ewp퇏yaDDOOo?Ձ𥂛rҊ.k-&m:'GT:T^cݓʂM!$6xcD ×ɿӭh.ۛϷ]$~k4x܌O~.-Tˏo$~>ib/h>-k{K)^R_fyK׏7A+d{qׯTۓU7]^: <]VNM5*6L"Lb"l/xZ>ۏayy[_^KDrwAR_&ɷo( ת)_~|;|l|&_~O屺]{P)/e W_3~U2ߟ?G}=CoAܔ7-) }#>{7.n军hZG~~}LJ'oߣ\% @]ؿ,_~Ŗ~y kg|`~.Fm0H?X)4_נ%rKAO^H?8^Da1?Tp9D$}W8٣Nßz6]w1z ٠kH-V_7^?~|  6kܾrqO/s;|K_Bk_9$ߟo^/O?痿OP6sd.VJz?1՚| ۷oQ%B/oW ^[?~<|(~kGȴ@e߀syޗU8)^<={ti7n eqṕolkPp:} `ZS̾)Qk@مgD3[Hsp{x د~?W6?+Nu͛W]=#R3篊7#~y~3~GN{ԯ-\Es=<7F3:"tdz ̯d~ nG~u7@ !O:_~`@?@ .cۛ@M-tu {an ؓ7K4b /!R_YnR[GDl7I1qdH!j^@%XA?͛~3[dm}F֭U<._j7OqBFH+ҡC9ᯗQg>~G80-2x $ؗϏAm@'䢉#^^o_‹\߫_-uΘD׍|0?"hxo= ȲN]/@eON'Y3(7c!9¼˷?i?ޜ?a/P{z˷oXȭa7'"V?_EWq—7+/_܄-FO=y3+r|=yI'c>o2&!{7No} B_YojTXo}wP_@O MYs$ 틯0an{s;춸r9:臘Et1cය?XqHOӃmp#jO [szyo/؏?~_> ~z ^yP+٧'+R`) .ۦc!Hq/{AY09'D\F^0)@o5W3`?[z .OMGooUH ^y N&^ݽr}@Sc&_̛e$ոiTY3[[S3@Znjo~<@tipnU*C_|,fu/o??)U Lq}|({FC?P_"xA @<0%0ݿeB>~A8)^" (V@ Dճ[ .t_6m Y`={޽u}ef!XN+<}|5"|Q>#pOB*9>`bQBc(g γ RZ3VРp {:3EaTNژ3| D.xTƉBͣ7t|?_ү2y5cඁ|3jq=VO_ӯ~_K"Oo&m" c+ï>a~&o_+8}~z&܂~?_߂z~yz6+isXG6=+/`-c ~ʯ߀_9.`o~?ƀݷkءG_!=8]W?g g~{ ~i_ruJoYegs,fKVwE^]˹i<*^]'Y|<(z_0F{hb~h`o \N~Mk#Klջn6j㵊W4wymDUhIGKJtOmdS8eõb4pTHpثfM)U$yJWk+DWئIjI}`2s+h9g_vUgp:xݬfq{ã).@^~3NF"FzFϳon߹gA>Jvm|^!5a`絿>qR*xi˼e -@}fBMA(UOq&NZN[  zzÛW5J`*P_kQeOx_(lټNk8JdzXf8UOI1G3!/.fn`ۓt aǚxA'`ZbT6Ev'Yn"Jt8`;I|K83;'oֲd]64/ ! 'AY\ۦ*ڦ߁{/w7~v7?Î<.~{Wo?/ծ-VRrdC>j<2K~hDxʋ8 'ݭ``k9MW綷cݱ>8NW*MU\&]Iq<+vU~&;.<&~cZEyE(. K1LsHºd#jMRͧǻү*A۠Ks(}pk@1\P*~G".LKpHS71[m"Y*J0{9h5 mc@ ٟ8bHgcĹvJZz;q N!B%C \h+Bz~>{HTw)Ɋ-ð[`&^h2'otlwd :pd^'oj6VR;"XV]Cb1NJXR#Q2#T8g! v@%=N5Uƌ:tMA>\ϣX }${$2]UĆ+&G+a܌uO,^3PuM$v&k*~kh'P@ZPuzՆL!/EУIVxuT~@mC m\KorxmN.c;aw/`&Ww4!=/"D o H.@pL}eu3Fp%56Z ֹ_~5cNN &5I61}69+pL6I5$S(_6~!F*vkYމd ϊN`{z rs`q8}kc ,6/k|U2My-߾׃jt2Љ>vV 'n9aVȑ0;GQ:ޙwUd6[ӭj6Նa}jD7W·.4U7Ppº =0/ 2Eȥ} ,EV넬~b`EHV7<:cSmYy1yY:t8Bh…jҐ;9cˣ4ÚGl\%y(IyYp [ax%KLݸetJKc ]*H{ЛS; , >T[X/ٌ=\y #rg/@I8$Gw ڣ~(Uj"HH~Mր4@›IKn}*cbv۬KMg, +I!m\H2;~BaT1xq\qGE*O˰I f}̛y V(僵nW&0U$kךoJzb\wW l|“_d8P epN(]h9d+1!pǷ <ÃM8hd**BxqryPXzw[[tuD5ॅGalxRq}PgYd** ҫJ,-uNΌ|׎*<"dnGN_;Dy,s-S[;lQ5[a`Rdqg0;W+(ymsK8f-%b\äs"\XS U  Mm9+2%TjrLS~5Z_HK dej uѫuFlL녹qfL::9NDukQ5'e6lFs 00 NpLiz O]SiN]Jvͯ,9 uԤNfljyIw9s2r]iQS4 68ϳ.sb b)se.wte,af s*:ނP;cMĎ`K ǚP,{Ep_oB0}J?~w~jЯ [5onSe[yGi }E"wQ5`{Iϡ[ yaNu9ZMȮ"Ah`3/O%Aiܭ_S5B|&)(vtr6>UIߣɵ?eiycE !kYfND :8ch'E}dX+a{C m1(^Uv#5w˻k5c ՘1,)#.vkpU;C?1g.x$!WDvSQS #ҍ6>`L d L2S +|vͦX:Lg 8& `iCZ]ױByhmwIԙuݚC;xD.B %̓fōJו%!&o!yw!וOPN]z$uA mp\iN:ڂ_NL Ղ{(/UҠ%G鎗L] X8 -ԈBWwy#w<徣L*&P7n0tILwQQ`yMFlp2$9y,G_w?*V?j;l *1y~i@8y{Qmwm<p!t&cnuw[D[ ~Zd/J޿Ɔ7A/rP8=a}{7وq. s6 Rgll 8C!";1vqyq%ާ| /sg6[EKNF|kRc ik}}(~ Z*(Ek֩HK26S"gna *=Y0` 8h]+0>EV0TO0np#PniNOj`3N"= :u!"`I@*Ǐ :'76| "O0 !'/~_h*F'%2/*qD($ Ϙ;t踗A@׬4'-TќASu~I)"Gn\D~yU5~2oMX&<{TRSG5:0nX#dCzRf+16~V7e%&k:\REYe~UűPKzmܘ/ZvNSEĸ,~ ^9ËюL!B܆'cwݢA8DɅH L4o =odN.b1rkZ@gη~FMg˸vG~SׅhP~ǃKSO Uh u#o\lSZ5/ $* C ($3 q@O\^:7xsprG<xW$ƅVY9bɁ̄):眇 m FdIE4m/8+p{vm1[ N kWuP*;49^ŤhnV5I+ֆ{O t.3A⠜&Fdp<#[Q]N݇4QG ׻/ŎZ2IK'U e BT̾ @{cڲԿ ?3te0a 1",R0KHF-׋;gRRCY?~H$ )@qJ:0z:Rܱ{ԥHwM-M.^_;Rr}F GL_1v4. J!dkć eDCb _\Ithc霉WIl <`sd=̫ח="kr|NSe;|+u~}rU_bRxPo҆*q^V~rCzJcQ}V~йtwz2^ൽ=agp 63a^hs.7D0ܗZ~F六JЪw$m(yl*3*5򠷁/ingn ` ٨d7.] \!_:|r5* ΖOW~7oic0.>*WբNdꄩy$] %3SnԗSN# Lq.ı`#@ Iݸvy@~Jצ'h5(Tk̳Bjx zV"[%l/nF4-hvFo5%?v67Ac`C屘f@311j=}-H3x d`);dyʑ=RrƛEsfq;4Bͱ񭝣m<^/f~ij(֎_t.㔛4x }^Ő| _A˞&%ۀ[O\@BL#rz{L]N4IϮ:7TRC!Y:&vyܐ D䈉')5M|wZ^' /WQa%Tb W:/ Y!)p kzk9 #Bk#a$1Q.sk2o499Z+k'r>oyT qF@G&E|1?7W(H&n`TTwJ(Dʫ'sEr_;g3cA 8 lh`LT:˧٨QePwo.罪 J ;ѡXg~[Ż1=&ĺ8 TJIVFPgbg$jp ZB"-ukZS Has7;H蕄@ȺbjOGp=9(Hnsy\ (/{Tx,Ϳo߼}۷.R<04윁zev܏3U||pa`Ry 7jL_AGv^}}nJIm 1ZϞHu4ϰX-0zlk!kμVw`vʝI@OJ{Ռ E dsJ80[}!s72w1ԒNb) RWEO? O;EZ^Sz2-]*Xķ䁖 ];2q.`ME@0^C*ZժFjj,0+Ăta{1 n|M ׬ChQzxo!=tϰ%:iyc]](䆀FVL(+ *㰩N}Q's @{=I|^By^ISE0&lЏe:59GgEWl6 !&=Į t )k|q;%a(nnYu|",{kfڮA/:b"kM|$i`lm&0wP-lEb#f RgGaU '9<塠mQwġP(]򍐒٘+Lʔבꬮ`a@Bl M N @CeDppϼhzp JxN|?ھrH'Jy"%&>Fu/h9nnMs` juY0{b "q]82W9¨^_EpP$3%1 On0ΠrC=aulX$hZd&{/3s`!I5Ho <顝4b^ZfQ woe%2#anfQ.6q1J 2Z U ^Kԍ+YEh0xİdӰ()Rzk;6(W}ȠFcy$L W̥eq_{L>Aq)}ETLv; zw*o">mudf B$d&զ!͎}.ۈl;'=>xN5UjvZ(+b/opN`q)hM>R; RKvʢ bS ԝU{HuS&5 1vƴS Q#do{J X'f l.H0cdRَ#^\sW~}1Cuia4%W7j?Qt0~|vN9; 麍VAޱAȯ}&~41p?=030U.`0? *&cz6I&řwZ͓G=wAB4y&w7vЙnHH4Pb!"O8qW632f.6sb?pS0 Cg O83LlxlQf}X`3*+?C:9qUBSswux0[QmgHK@r{GR\+͜XV;MTֺz6v$`k]K"94lIpr"9oQ- 0 Nmlg .Z4<;R?kc ֱvb8rlmuQ*\xyKDXq 4͏jQzd űȕ@tT g Kt;]ƿy*vJ< Mנ'jл܊@ag4YPhYx<&wal yNQ!eiMy51z~xY +ˎwQ:4>y(PFoʿ2!c~;c_$AX)AȻTa"Xb*d݋"oW@P.%PKR1Q>'kzCh§{?b)ze!h3nbd>p} <uy*i$ a zu=OW2- p2уު+Π;U,@4HÆ )bP~8ǮГ+`F0o0Gg^ r0Cݔj&iH)L!| u&qxJ 9H)DIZC\ϋf[%9eV]%tDl{݆>p> sCHu! WQ7c 9BS;t\>,T=X[D;0§eGuI{" =R?\)M: BZk&E D:myҤYEeaƆ]2t^;;5hĝL8:jbl;s&`H4o*–yP+zmꧠNw'7t=wz#'锭5.Tz(`˻S$GK٢t:,`|(v>73ux\ׇsp6c3'o|G^'c'pOG:q(-pz~wJ$Q' 9'-腀DNwpr5ƑQN0DH \睤5)5g\M+e:~'X4abs^[a* G!qȠɊ×~B僬}$Q~ԩ빗u˱أx%ʭj;8)E`eMFOOSQ=``D4ʀVҘOh [&Ѧ`_Lr [wx `)MHR!(Gib6=CDO( f c>Fq1'ZbM7PDt1k18ܭS"q6 ~E~\WHxX_7jPׇ˝usWfTlK4Asul+Nf8!YZyl 2܋`a MoBGyZm\ˊ#ƴKgĤwzlL;᭯Ecp~aHTes&;Ӕu \7*k[*5rjX iJ@70Ob!n-M >ēAZ˲Giܒb6$2τ8M;} 1k0ݪmcl zW%wR@me%RH`T!oeO #YVbfգ4W'p: b|g`25BOޔZ ٥QBf2_=hIsv ]ͫ{IeC7Y&1Bwot*M5WdQ ƯkxR;YL_bz"1dYwN>3Zn@ 9|[7,̡X@HdJag.|<ޜERt8TfNۀCO=![nQd>)56WQm^Nl/$2XSWlиD"t,# +c* ޽BIAm8 gsGrL+n h^ڡ^kwrcr0@plG|HsHk:Ho8W pB;ۦKzeL$5nf^`GY$IKz4ԕdS; ?c)60l_BGEyӑ0 =F[V{de*XMNi?Пɗ &*ώbJBď;n9P Rv0 ]4# $#0qiC4QTҝq~B'|'Ϋ΀;i<β%u (=:/8?w6?{= nzO#g3׺*&Uum=k&?2@d qnL[r#UL)Txe5$[U +dl;'@~B ;OLy$<]hnStwz#l:g4#jhx 62 19ۑzl,MO: 6"XPYwԖ>&X9rsAv굸)#]#b5k.ZT)sip<)98aHf "C݉0.8Ov|p+ ,LglyGtkkWAwyȍ8lSPST/XL>22ME/$ ;kYY0Bs<|Yg4=)'NrBgcy+CkqZjNhDfi 6&yB~t ءq1"d ܖdHi"@,w\? eL>ۻ鏉#6&cDh1wۄNq];8'*DM }gaL,B[7]]0 byau${:5( ,-pMʹeEG%zfsU7Ut4|VKs7ӫ:r=}Wfw a-@D 5T;@ۜ-Qq1 U5w[ge('ȧFO>U G4'(_@q_=2t!FzHDŽMͲSQVMn*{CpEۿmX: ;e{Nz펻6砫=pp 5#'vy.bi'>ڵzh猥8Mʠo}N9.h$$x@v)0{eΙ&7.9& ?Ϥ4=`%#~=(V^U)*=/NEo XI h6V?J9ĬŇ&+434_T+ܝ:jd%Uu"F6NUs7DbǞ xX̌Gx +/S!|,lDZ[Mc Zm sĖ|A>8=14 hośV5FY%5lmX{Td/IѮn(.=s ;tL3o%yRlFL9F 9EU0͇^Qi:blME0¨=VJ9\`ڌ=z?;|,#$=7iYl/XpD0mk9 " b/ +{. z555R+V:d󆛯 &14Metf*`7Ȱf ႛvt4S taJU&rD6PXQ8`ʦ7$MD)68@q?O 2w,gC8# S׫?hpl;Ti'H@ٔPf{=&QY>#rUmjҐf¼@w4ۼTy7r$VIN띿xأ cB%sus PQ-UYZ3^1#,< ;}%>Q$\V.+ ̎)ԷYQZ̀w8úH.< xt=kf@,+ݰzvp0w[ NCG\:hٺ0|QDi3a &Q2sL>`}|EG1Ǔ(K x1t14 4݆z.*$sB;;-@\cWEyQ Ovd3>:|yzl$W7n^4*<]񝸦Yg$5w[gG1 P{{M_,eD>b'Х1WdB*Lwui+F?\*Aɉ \ V'ڝ(uJ,A\#H'[k[a^J [9 Z{@oÁ\tUӃX_?]kD}VH,$Si2v$>2OFf#3t@,?n٘$5X1x][:ΨtJ!]-E'q= Ƞ2h4\II :˜)y8x͘Tig#5]IF$DSR. v &:a EIv:7iH%( ! .ԁ4hN2[aH;RȽ:iλ1!cP.$*E(̺t][jL $ c ҷiAN>NHP6dAK6KC%%}%=]R Riw}i:QcKSCp$[~8d8 OGgeA/ e^nqgE^2 J-n\j'Dw ? W0e$Kl\&|^!naphV10C&/ޒcdQuӇap.$j '=uov˂鞦|{#*0 6wbP@ւ:P S0}=gEH*ueGg P3l:"vǭ]k}MvSoAb^--7_i[jm7m>/93>] I` Ĭ>sP$ FVĈ! C' q L}Dg!RKUCkЎy7F3rZ1#_G$# xp?ps|tkάKuC?x2w4,#l uW KHCX"zd=pUȊ81a|BI8CC% k~:3fshϺ΅ul8C xScl\%1EVxCӻz<>9k- xPrOjdaI^Hq9cڠbbL0tʡbn#XXԂCuH?Sr)\p.ݽ4{۝ A\d :ޏNSjq xq@tX򌊚7[({x&b'vײoX 6{h"ފyLq ]|uzax`#Fp*){|l{$X.U{9AN}aVt$ɡC ^Op}I{nU ?c4o8}R"FvY씢ޯRKYq9)-Wp? L,Q3 H`8@~40cĠ8 k291Fmw1n Ȼc2; &BKCE2IgY QXj6<yt 4I;Iǻ 5yzБ{{s/ lcFscqip;u26wy Bv`CI"%N4{CQ45F ^c[;kxѱ*1v *-v!Kl^˼]WQ}{l+J&UOU1;pF{S, $at٧a8N}Ap{pl6WލMo6kiH \@) 'y͘HV]湳m6mۮm(t`]P:3nf]Тh?4ɮYK;t@ڬ-Xy31/{L ~GӇ HQy2$I߉FAV'Bر1o:c}+&fEw;ӥB&u[ TDfh|w0+` *phԬ6H ܸtBv _va.hyE\M\7b]o0`?tϻ#>gk7P.^^IrT(1.P@G(21@6U'@jc[`0칚qU[\gpYl]nwȴ)(YSW,m-3]YPEy`i4¤rSi\dfQG2މ̾eP rW{0vR' S#c\|7ĄG0 8~ Ȼ;3tSlLL0,y&Dn221m_89D?'(|:̧vjr%y2!\̐#GA懭|Ƃa=8ʈi<1TA݅I;UTZlض 6uJ.ل?@SDfVHPDCZ8". ?pɨ˿t&IE&vUMQ1`4! 04s}WM1 ԋw"Be:(HfyF9J. m\$M&=ӯ'S Z?$huu!\]صtWĆtin} `{쀸-}JH]i0Ыp0E5RtF{jk 侽sv3C,XZw+^I 9Wz 'ޮIGp{*)̷K -pQaP3b#2kSL=\Q%x2 #kX;8:tΦ}1}Ȯ-؍FRGoijqe6WI8 D+NOi0.CvPQWlx| 8c̶bWkG+]oc.lEџ{ !Þns<!/l闀wQžI1uCElrȊl,UbLT|t36 J&P߯OH|J0ygg Sj 4u 2`a\!em F1dgݜܻ;,/%f4%^4!kە(F+amw2<c:s=.4FH*2h3ƥs"g:ztmvW)ezҹyYD(ڠ͓nI\sT1bx?c[qr>$Zbt"Sݔo.ΣI2ϭ?eY_H( =<}Nާl$m"L-zB-Sq<taNc{EMQx)êʢfCh>ۀۉf$Mr\7ZzEI5H"ql>?:-Hp\tFwłq5${B/)<3A&LK6b!0qgQƷ{ԃǵtGSp1 `xb8lV`pFH"MR4R UyG"pXAG BiǎXGC;@'~MwK\ܓQ1Pki뙥*D5yӔ`M)V 9ƕÍ]AdRoFي. +ԁ\Rf9B WzM7 I8uÑ S2zK0U’"2{iU~9W;#Cv}3r|4{ >vh3ǿ=f `3D c/G|r9X -6hf+؁ a|")jXǚFb = :K_ J5b!3dhBLΝ)&iWP-b⤘L UX MN.V4ÌqOGds1O6v-3] jR|X J;'ƁgF+^94(D7lt}SF, >wg]Hv.&?M OlC?Cu\ 1Y?u":eis@[4c7:`:N)_{Y{rsiv 93; qcwX;]4Uq՚ *3 )1l8k瑣$H&Nz1;(~JG~1=(:82ӂka Oכ"pTL8s<n%Ykدo8!éf/c>$ Y ^LD.\Kݧ2 @:3jcž%`ւ67\#)[#-޳'Xs=?NzsjYt:w6ZQ[K,uJPdu|-Iz٢߆oWzg] J`[ܜ'pq㻤$ACV5qM 2?2ߡRtPmVi"sFMFRʑG 8{?mv@(w%@ tgeR 5..BP>ɩ=_` ^&V=Y{dp9qHH ܀A0LH{ӄp;Yɝ.1izkQڅ>:I*ݪ{TTj"`fhVxh0&[9Z)mqwckgrpao2m{ґ'+d("sʀmcAxE\ˏN'˟=tqEćfs0g]Mv~af hʚ1FNwd =],Z6RQ = 얪D/]TK,3OSS:syDx76pyU|+cF%C FRnWd%+<;SZW,QX.R7+hߧݭXv|[%k:qE10JӼQCOlcu7>gxz^юˠӫќw{Cc(:Ū|F;2Ⱦs@גoM$ˆ鴚  uM64:g>3Cq8ޠJbO>l'-] ❟La=|kg]J (>(W}N8o`jZdN,Lis I qyc9R5l?RמHѱ4$PTO$opͫ/zEä(>>indq)Ƣ'%OtR54ø;];(nrvg&E"NwSgz9tizE~Ì"n"f9ϼM5 m ʀv<{;&{iɩ wᘡ1C{6Wb*L* x>vAUv'#6Qw٪Sm;169fT=KUuwY\;@Avg,J-]ul'꧵[o“Bҽc <ȸa529|EѨY$=\ƬJo:NKp1C, 1> FnY~brw(: B$xBT@Y$ tjZݞ:I6ݺIn+Y-@So<9M!y!r U?O$ڠҏ1۞  RGw  52 IidN ^J(&qqq !yJ*ʦn2M#|f(?"^f"tSR춥LQQE]+IG+{_GQM$xFz^"3t%G;MvWO;AD@%Vtlw+MKNe%r#K0d^TSvu}&=ʹfFH$o陗j/OggJi (]6;j@"s>}d! ueJ)Jt>\=b_,-bkTy'tRBG'=wܱ-dKEA9`B4IrNL~|p*9IЕ>bsnS¼U ض8Q疺K-a< ?=py<^GㄊP6P JLA^I3p669J'O.E okrRa(>;T:7#HFp-RsW"#P'(tFA}X3nO$i1:oՌs@3'Z]"s]B?2ip -!.1&z֧/ -E[,"y4b9H<*l(OwS>szO~<@랒Oa} (!D\"lםFҤaþ*<.?RL6 N4u'oBe0!s/E!$L_ϓ6Z%vMA%hHPq,X2mF'1%206 my&Nf?_yzI!UbEl7txRi"OC xs's"y8QNSFI>h R CvAveeY|0r%mxƜySEgxrEWAi~Kd 'nJ%?@$Nqα.{P>Bl][$>ao\. wRhjrsk< `D7q&1[4>KlEayt|.35CYK~ʞ_إB\UP\9DrwÜD C'7qJj&4B)NqA=%'r0" =ovq'{z0, =GGE+9D;* lAC tBR]#*ҿm.n9`pQnBtO~edxhTVY1ϟףo@![ , F{K'(`˰˜VpS'OpEnfsEScS5{pJ L'iH [_\%1ȄUF6n˵Y$ce:%}/(&Irw#x{هB1Uz5(T F>#Ɗ>LBus A fq EzƁ2{q\#ܙ>0s#^\sW~}ѭhm~钧X"Ů4tw.yOyI'm{vJ%?uƵz@TL'Yƍ#{8̣Mc7ը:{vfF+Yx6x2 %9'ֈVyxk#ys#0٠8Y9v0Xk&Aݑc pKhgm\\A-p0Ǜ"yY Nj݆Y:wNgW$TO^tj ψxxXfAaeX IV]i4G8þCC`x.GX |/!B3kY܋2GPT]Bb޷=AE6]3Nod%_H9t8DN!ʠlİǵnL>AAEh1|Pw(Aqg3]&[MiRDـF]cT|tq=$(l+ Na項8A\T lNB)ӊ%8'5([q>5$ B:}H :/pՃM#g%[X_0􏁣9A fW8ChH RWtmdW/Ǝ ¦ Q1>O6-\\+t*"FG3F@^i"n$剩?d&u2;Ni\՘ 'wL~Xgh>+j&vJDfLwjU^3|ßV5gm_&+4ZmX%-<HWa; py2*:wI,Cȁ&[26;ԇۏ3䮂4&[46g`FH*r?zRuMvn"af{bMG0P9,[@q2x7/v' L]"Jx\/yPG!cVY]P/)iH+a {7ehG}D<+m3~<.\3ODD*sbXegYLWEs^="k󅜱S |XzMC^ !e2_(&Jב  ~ijQIg'z6ظYγXWmzaP&&a6$h&S25}k66'Z N=OrZLPQ'98/=ˌ;Fa;goxob8X"F蒑q@N,h,ЛqAOt|ٺ-"p(3JmeRCYw|eh%t\ K6%Jf678IoD:ﮚq4KρpJx#w%P7 innf|6EsF 'tLp*0lItw6d.>Bȷn çGzl*I5eC`/[ʪ$KČ)J!- qU",z$u# 6ZgAa6HٻTc J$5-P>, EaB'ޯs7T0d%Q>P>Ye?ԸD3쉃}vNDh0p@oBu}͓fHR#R>ZUt]BO7F"Q(ZmC)㥘ę$^Irb 1_ɧ1/R9z"KR.$pߕ} L,658:O v't|Bއ&f $Myyd=a f^N_i鋧557u&07$&1CbTUtRUҺwFf6NҼsr9hr:bDNt Fvbh.ӥH.)۵iE|\*μ}WC2ZI>əVaTӬ$K6Z䧰(3}S88pע)}DN8# arX -&& ޔjxH⌂RS4L9wҲ:78qi4M)GcL.Ƭ$^`ܶ]8;2:|ãW >avi"8t5N T\>vL dG|&c<$,dkeʺw+cw+g`Hv" =#-Q6Awk#8cbPd,41``^N_9YsX3= BI F;Ai6h`2jLqڨF)vG-L);[sZ*Eׇp'l]\t=JHG.L gu($o?}`;wR)gcyI&AM4adBI8 +҄=^k7-sh();Cs۪Y Rn*Wnv}F#\>'MV.j vg!*jX=6F  H%px߃\"sGi zQ.!ty|t"^i~ w l׆0CBBUx|٠C , ԡ]@qT2 #c['CS^ȶTik/^g(ڃ*tw%A )Qp˩=Bձe@(mZc8$1"F$qyޥin#,'i-ˇjނ H9LLކ8:uC&30{|o&4qfo4 TY5ԙ7neҍGGMe$U:_;6aZP4"zNjTsDa=M#dgUL qq;}{E'Q(Ա=$~OLInѡ~.y}/# X\wTL nHI ֠>bJQ9ɁVCQz 4@.,;nCcdd)<8pZ rgf3c!Y慳gAZE,7:l.pdO hY&ٝ5LS`Q,dD@NtuQWSLm68Cz[bgxW00V ]d:"V]]*&wyQ9KS6+ԩq-Ǿa]<!4 3tDu`dž} 5v/zd=qWsUsl}M ĤÈ)J 9}{ Љ2CY+uF=`C"ZKѧscXNE15/ \wy9i@N%`'W5 }>R֖ ,~լcPtwyJxn[Ćr"ؠ F03&<\gRQp ί+t<\ l0C o i*Bbq52f j$ ĝzs`clDGnϧ_GV˸3{tt'uHBҐ:W|u9{STq܉3BAfϨ Hx'+idĚb:8Mf:e>żl8Ehe Fg뷠^inUnlr~u|ܟ :'&lýރb@.5ŻUpQ^\0#MP 0ռA.J%H>0jQ@ F}䭆_ ;=5ZeT{sӔh# $yܔ|z+I|)<6Ί{v͇T8A(̓uUǩ?pKCΎ}Z&'~rYUO5>:lՌ1%f!g*ƒ}SJ1[a朓\%t=#xco0Hj%jXBw|QoBO'r@bQc2kFaE!/<2i/ѕ{&Tl. 6] ĪA3$?Y &c0; wS0`0 ZBwt 5@T~sLFC>2Z7'wۂKڂ(|,){Q Aw B4akZT&ԤNg \/kTzOU%U?g*Q\` +yC¶(Lp:$~MRP9L8vCT5ϑֆ;(lEe\huzSsb-sg&2ŮN'+n6Lbu0 rLj_yqxpx]缳JB[ H32y7FD<(10a8!ZE\,֌v͂:܍ A)&!/t* ƘrX#SCF*%xTbq [A/%qhx%;WŔVMOu5 фSӉi&YRK. txC\mVIțWYoj;n|:j<V=n6-G 属23jIÙ3#7W>zl0'=ZJD<-&elqjL9?:#MzA|s6MٸxKz[y"!PFq܈hy#?[<O1{lΚ `3vͭwebg,s mUkMnqX6Z[`KqnYTaٻa?E4aeպ5 8riܪ5˵V/]LBKgF{}1doL^UUtSկl6b1c EaRjOĽfe o;*C㎜_6B9aةLM)d uDqsc6Z)!eqj$+݄WxNۮKMv9RLmlAa[Fot|l3=% .mwC$Yؼ*VF\/F=brOܪ@m{vF;hO{sl#h~$:UiXTBצPC%⛷ҐBztPLΙ >+';ݻ>:j Hkþ+m:bEN P$$ !Z߉݈&ws:/wy6Zjz!6gH_]:gJ0BԝRd%juRh{'ٜ ]q- &q]H!`A\uOaGboAM UH]c`Bۛ~3yh4f%f%YI@W43v4"^1%4sLYo^Iˎf۸ۑ!f2gF6"3Auh~*>i绝ok]oV|47) >f]G*զowa{uWM٠)pٔ =ɫ.|lʢrA/\s.w o;On^ y$%BG^2u\ [DW2k` hÅɜs&7Ttc27t9ɇ\G~CGF6y-nOv5%0y!H/kOSϩ7RzΥy1g)3yLL֞<Ū;"E8Yi/TvGŅhK*j YJG%MlۚhP}`6[uOa/IUrսZP,Iїwzz݆k+lY'RPUNtS2T"+5=E-%xJSqӬVmj2 hK^n9&e.k'f,C@f:{M X~xN84؉fҿ %msogP/͆ s=,8IBt_`XRpkΆi<덺9VcTwÉ :]X_|< >CAN]&Oׄp4I[Xc~9C.[-P"cǃBo {1Q@|BD=ȰSOwa1OW%"}4 ZDy"ƕqom0 /^:DYǰ=k9 5EmxPj/t611M^{~1wjrFX{ɹqe7BH![$+ilWAf!qc*(iG8 ;ʩ=f5A aΝV?V*2ZKZ}߼vÛWo_ NMTm:\%bG,EjlŗC 4Im#_c2A lØ s0k?`t#!.ݸ`ڥ;\YҮYmvTo$q^*(YtkY/ Q[j"MSN" uczu SL]zﭡO~OMkkĉԤư:.&z*ܼyo>hXoo5Yݿ_~=Qb;aomU܃mqD8oN7r018Rj]x-Bah{*)>V{wPuLC(b{ Z8a׹p7R903@|$ؖT$Z}FP:rpзI_D6Coմ<#zFVJ0Tq5x=:z(ݖ"Oȥl.juSPp"~EܽV`OFצ׶=ѝ̾h%kg0M ==Zlv- legacy systems – Capten https://capten.ai Thu, 02 Jul 2026 05:23:37 +0000 en-US hourly 1 https://wordpress.org/?v=7.0.3 https://capten.ai/wp-content/uploads/2024/11/Capten-Outline-Logo-Icon-100x100.png legacy systems – Capten https://capten.ai 32 32 Why We Built Capten.ai https://capten.ai/blog/why-we-built-capten-ai/ Tue, 16 Jun 2026 14:37:43 +0000 https://capten.ai/?p=33924

Over the past 30 years, I have worked with many organizations across manufacturing, healthcare, energy & utilities, financial services, logistics, telecommunications, and government sectors. One challenge has remained remarkably consistent regardless of industry: organizations struggle to modernize their applications fast enough to keep up with business demands. 

Many of these applications were built years, sometimes decades, ago. They continue to perform critical business functions and often represent millions of dollars of investment. The challenge is that very few organizations can afford to completely replace them yet maintaining them becomes more difficult every year. 

During my time building and scaling technology companies, I repeatedly saw the same pattern. Modernization initiatives would begin with great enthusiasm. Consulting firms would estimate multi-year timelines. Teams would spend months documenting applications before any actual transformation work began. Costs would increase, priorities would change, and projects would frequently lose momentum before delivering meaningful business value. 

At the same time, the emergence of Generative AI created a new opportunity. While most organizations were focused on using AI for chatbots and content generation, we began asking a different question: 

What if software could understand software? 

And what if AI could help engineers discover, document, modernize, test, secure, and transform enterprise applications much like an experienced software engineer? 

That question became the foundation for Capten.ai. 

We formally began development in 2020. Our initial focus was not on Generative AI. It was on solving the fundamental challenge of application understanding. We invested heavily in application discovery, dependency mapping, business rule extraction, automated documentation, and software intelligence. When Generative AI began accelerating enterprise adoption years later, it became a powerful addition to a vision that was already well underway. 

Capten.ai was not built to replace software engineers. It was built to make software engineering teams jobs more effective. 

One of the biggest challenges in modernization is knowledge. In many organizations, critical business logic exists only in source code and in the minds of a few experienced employees. When those individuals leave, organizations are often left with technical debt – systems that nobody fully understands. 

Capten.ai addresses this challenge by helping organizations discover and understand what their applications actually do before making modernization decisions. Instead of treating modernization as a blind code conversion exercise, we focus on preserving business knowledge while accelerating technical transformation. 

Another challenge we observed was the amount of time highly skilled engineers spend on repetitive tasks. Documentation, dependency analysis, test creation, security reviews, and impact assessments are essential activities, but they often consume valuable time that could be spent solving business problems. 

This is where Agentic AI becomes powerful. 

Rather than acting as a simple coding assistant, Agentic AI can perform a sequence of engineering tasks, analyze results, make recommendations, and assist teams throughout the modernization lifecycle. The objective is not automation for the sake of automation. The objective is enabling engineers to focus on higher-value work. 

We also recognized that modernization is no longer just about moving applications from one platform to another. Organizations are preparing for cloud-native architectures, intelligent automation, AI-driven workflows, cybersecurity requirements, and increasingly complex integration ecosystems. 

As a result, Capten.ai evolved into more than a modernization platform. It became a platform designed to help organizations build the foundation required for the next generation of enterprise technology. 

Today, when I speak with CIOs, CTOs, and engineering leaders, the conversation is rarely about technology alone. The discussion is about speed, cost, risk, governance, and business outcomes. 

They want to know: 

  • Can we modernize without disrupting operations? 
  • Can we reduce technical debt? 
  • Can we accelerate delivery? 
  • Can we leverage AI responsibly? 
  • Can we preserve decades of business knowledge? 

These are the problems Capten.ai was designed to address. 

The future of software engineering will not be humans versus AI. It will be humans working alongside intelligent systems that amplify their capabilities. 

Organizations that embrace this model will innovate faster, modernize more effectively, and create sustainable competitive advantages. 

The AI revolution has accelerated what’s possible, but our mission remains unchanged: help organizations understand what they have, preserve the knowledge embedded within their applications, and modernize with confidence. 

That vision started in 2019, continues today, and will guide the future of Capten.ai. 

]]>
The $100 Million Problem Hidden Inside Legacy Applications https://capten.ai/blog/the-100-million-problem-hidden-inside-legacy-applications/ Tue, 02 Jun 2026 15:06:18 +0000 https://capten.ai/?p=33937

When executives discuss digital transformation, the conversation often revolves around cloud migration, artificial intelligence, cybersecurity, and customer experience. 

Yet one of the most expensive challenges facing enterprises today rarely appears on a balance sheet. 

It is the knowledge trapped inside legacy applications. 

Over the past three decades, organizations have invested hundreds of millions of dollars building software systems that run their businesses. These applications contain thousands of business rules, operational processes, compliance requirements, customer workflows, and institutional knowledge accumulated over years of experience. 

The challenge is that much of this knowledge exists in only two places: 

  • Source code 
  • The minds of a few experienced employees 

Both represent significant risk. 

As senior employees retire or leave the organization, critical business knowledge disappears. Documentation is often outdated or incomplete. New engineering teams inherit systems they do not fully understand. 

As a result, modernization initiatives become risky, expensive, and time-consuming. 

Most organizations assume their biggest challenge is rewriting code. 

In reality, their biggest challenge is understanding what the code actually does. 

This is why so many modernization programs struggle. 

Organizations spend months or even years attempting to reverse engineer business logic before any meaningful transformation work begins. 

The future of modernization is not code conversion. 

The future of modernization is knowledge extraction. 

Before applications can be transformed, organizations must first understand: 

  • Business rules 
  • Application dependencies 
  • Data relationships 
  • Integration points 
  • Security implications 
  • Operational workflows 

This is where Software Intelligence and Agentic AI become game changers. 

Instead of manually analyzing millions of lines of code, organizations can leverage intelligent systems that discover, document, map, and explain complex applications. 

The result is not simply faster modernization. 

It is safer modernization. 

At Capten.ai, we believe enterprise knowledge is often the most valuable asset organizations own. Preserving, understanding, and transforming that knowledge is ultimately what determines the success of modernization initiatives. 

The organizations that win the next decade will not be those that rewrite the most code. 

They will be those that understand their software the best. 

]]>