diff --git a/release-packaging/HelpSource/Classes/FluidKNNClassifier.schelp b/release-packaging/HelpSource/Classes/FluidKNNClassifier.schelp
index cc49f8e..96dce16 100644
--- a/release-packaging/HelpSource/Classes/FluidKNNClassifier.schelp
+++ b/release-packaging/HelpSource/Classes/FluidKNNClassifier.schelp
@@ -145,13 +145,13 @@ w.front;
 
 subsection::Server Side Queries
 This is the equivalent of predictPoint, but wholly on the server
-FluidKMeans is accessed via its own synth, so we need to use
+FluidKNNClassifier is accessed via its own synth, so we need to use
 a bus to communicate with it. The inBus receives a trigger to query, using data
 from inBuffer; a trigger is then send to outBus with the prediction in outBuffer
 code::
 (
-~ib = Bus.control(s); // input bus must be audio (for now)
-~ob = Bus.control(s); //output bus can be kr
+~ib = Bus.control(s); // input bus
+~ob = Bus.control(s); //output bus
 ~inpPoint = Buffer.alloc(s,2);
 ~outPoint = Buffer.alloc(s,1);
 )
@@ -159,7 +159,7 @@ code::
 //We make two Synths. One, before FluidKMeans, generates a random point and sends
 //a trigger to query. The second, after FluidKMeans, gives us the predicted cluster //triggering upadtes from the outBus
 (
-//Set properties on FluidKMeans:
+//Set properties on FluidKNNClassifier:
 ~classifier.inBus_(~ib).outBus_(~ob).inBuffer_(~inpPoint).outBuffer_(~outPoint);
 //pitching
 {
@@ -177,7 +177,7 @@ code::
 
 // to sonify the output, here are random values alternating quadrant.
 (
-//Set properties on FluidKMeans:
+//Set properties on FluidKNNClassifier:
 ~classifier.inBus_(~ib).outBus_(~ob).inBuffer_(~inpPoint).outBuffer_(~outPoint);
 //pitching
 {
diff --git a/release-packaging/HelpSource/Classes/FluidMLPClassifier.schelp b/release-packaging/HelpSource/Classes/FluidMLPClassifier.schelp
index cc94a63..ebd9f2a 100644
--- a/release-packaging/HelpSource/Classes/FluidMLPClassifier.schelp
+++ b/release-packaging/HelpSource/Classes/FluidMLPClassifier.schelp
@@ -86,7 +86,7 @@ EXAMPLES::
 
 code::
 (
-~classifier = FluidMLPClassifier(s, [6], FluidMLPClassifier.tanh,1000, 0.1, 0.1, 50, 0);
+~classifier = FluidMLPClassifier(s, [6], FluidMLPClassifier.tanh, 1000, 0.1, 0.1, 50, 0);
 ~sourcedata= FluidDataSet(s,\mlpclassify_help_examples);
 ~labels = FluidLabelSet(s,\mlpclassify_help_labels);
 ~testdata = FluidDataSet(s,\mlpclassify_help_test);
@@ -151,3 +151,55 @@ w.refresh;
 w.front;
 )
 ::
+
+
+subsection::Server Side Queries
+This is the equivalent of predictPoint, but wholly on the server
+FluidMLPClassifier is accessed via its own synth, so we need to use
+a bus to communicate with it. The inBus receives a trigger to query, using data
+from inBuffer; a trigger is then send to outBus with the prediction in outBuffer
+code::
+(
+~ib = Bus.control(s); // input bus
+~ob = Bus.control(s); //output bus
+~inpPoint = Buffer.alloc(s,2);
+~outPoint = Buffer.alloc(s,1);
+)
+
+//We make two Synths. One, before FluidKMeans, generates a random point and sends
+//a trigger to query. The second, after FluidKMeans, gives us the predicted cluster //triggering upadtes from the outBus
+(
+//Set properties on FluidMLPClassifier:
+~classifier.inBus_(~ib).outBus_(~ob).inBuffer_(~inpPoint).outBuffer_(~outPoint);
+//pitching
+{
+	var trig = Impulse.kr(5);
+	var point = WhiteNoise.kr(1.dup);
+	Poll.kr(trig, point, [\pointX,\pointY]);
+	point.collect{ |p,i| BufWr.kr([p],~inpPoint,i)};
+	Out.kr(~ib.index,[trig]);
+}.play(~classifier.synth,addAction:\addBefore);
+//catching
+{
+	Poll.kr(In.kr(~ob),Latch.kr(BufRd.kr(1,~outPoint,0,interpolation:0),In.kr(~ob)),\cluster);
+}.play(~classifier.synth,addAction:\addAfter);
+)
+
+// to sonify the output, here are random values alternating quadrant.
+(
+//Set properties on FluidMLPClassifier:
+~classifier.inBus_(~ib).outBus_(~ob).inBuffer_(~inpPoint).outBuffer_(~outPoint);
+//pitching
+{
+	var trig = Impulse.kr(MouseX.kr(0,1).exprange(0.5,ControlRate.ir /2).poll);
+	var point = 2.collect{TIRand.kr(0,3,trig).linlin(0,3,-1,1)};
+	point.collect{|p,i| BufWr.kr([p],~inpPoint,i)};
+	Out.kr(~ib.index,[trig]);
+	T2A.ar(trig)*0.1;
+}.play(~classifier.synth,addAction:\addBefore);
+//catching
+{
+	SinOsc.ar((Latch.kr(BufRd.kr(1,~outPoint,0,interpolation:0),In.kr(~ob)) + 69).midicps,mul: 0.1);
+}.play(~classifier.synth,addAction:\addAfter);
+)
+::
\ No newline at end of file
diff --git a/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp b/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
index a4e0cb5..069c01f 100644
--- a/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
+++ b/release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
@@ -156,4 +156,38 @@ d = Dictionary.with(
 //We should see a single cycle of a chirp. If not, fit a little more epochs
 ~outputdata.plot;
 
+::
+
+subsection:: Server Side Queries
+
+code::
+//Setup
+(
+~inputPoint = Buffer.alloc(s,1);
+~predictPoint = Buffer.alloc(s,1);
+~pitchingBus = Bus.control;
+~catchingBus = Bus.control;
+)
+
+(
+~regressor.inBus_(~pitchingBus).outBus_(~catchingBus).inBuffer_(~inputPoint).outBuffer_(~predictPoint);
+
+~inputSynth = {
+	var input = Saw.kr(2).linlin(-1,1,0,1);
+	var trig = Impulse.kr(ControlRate.ir/10);
+	BufWr.kr(input,~inputPoint,0);
+	Out.kr(~pitchingBus.index,[trig]);
+};
+
+~inputSynth.play(~regressor.synth,addAction:\addBefore);
+
+~outputSynth = {
+	Poll.kr(In.kr(~catchingBus.index),BufRd.kr(1,~predictPoint,0),"mapped value")
+};
+~outputSynth.play(~regressor.synth,addAction:\addAfter);
+~outputSynth.scope
+)
+
+
+
 ::