“Fifteen days” is the kind of claim that makes experienced L&D people narrow their eyes, and they are right to. Anyone who has run a course build knows where the time goes, and it is rarely in production. It goes in review cycles, in the SME who is travelling, in the third round of feedback that contradicts the first.
So this is a walkthrough of what the fifteen days contain, what Flipick does, what you have to do, and where the clock stops.
The four stages
The pipeline has four: you send the source, the AI pipeline runs, humans QA the output, and the course deploys to your LMS.
That is the shape. What follows is what each one actually involves.
Stage one: you send the source
You send a PowerPoint, a PDF, or a policy document. Not a brief, not an outline, not a conversation about what the course should cover. The actual document your organisation already treats as authoritative.
This is the stage where projects either start clean or start doomed, and the difference is whether you sent the current version.
Two things worth checking before you hit send. First, that the deck is the approved one, not the copy on someone’s desktop with tracked changes still in it. Second, that you know who owns the content, because that person will be asked to sign off at stage three and you want them identified now rather than on day eleven.
Useful to send alongside the source: your brand guidelines, your LMS details, and the learning objectives if you have them written down. If you don’t have objectives written down, say so rather than inventing some. The pipeline can derive them from the document, and derived objectives that match the content beat invented ones that don’t.
Time this stage takes: [confirm typical duration with the delivery team, usually the same day if the document is ready].
Stage two: the AI pipeline
This is where the deck becomes a course. Narration gets written and voiced, slides become animated sequences, assessment items get generated from the content, and scenario branches get built where the material calls for decisions rather than recall.
Two design decisions are worth knowing about, because they change what you get.
The output is source locked. Every word in the finished course traces back to your document. The model is not permitted to top up thin sections with plausible-sounding general knowledge, which is the failure mode that makes AI-generated compliance training dangerous. If your policy is vague about a threshold, the course will be vague about it too, and that is correct behaviour. Vagueness in your source is a document problem, and it should surface as one rather than being quietly patched.
Assessments are adaptive rather than a fixed quiz at the end. Learners who demonstrate they know the material move faster. Learners who don’t get more practice on the specific thing they got wrong.
Time this stage takes: [confirm the working days allocated to pipeline generation].
Stage three: human QA
An AI pipeline with no human review is a liability, and Flipick reviews every course before it ships.
The internal QA pass checks that narration matches the source, that assessment items have exactly one defensible answer, that scenario branches all terminate sensibly, and that the SCORM package will actually behave in an LMS rather than throwing tracking errors on completion.
Your side of stage three is the SME review, and this is the stage where fifteen days becomes thirty.
The way to keep it tight is to decide in advance who reviews and what they are reviewing for. One reviewer for factual accuracy, one for brand, and a stated turnaround. Circulating a course link to eleven people and asking for thoughts is how a two day review becomes three weeks.
Time this stage takes: [confirm QA duration] on Flipick’s side. On yours, as long as you let it.
Stage four: deployment
The course ships as a SCORM package that goes into your LMS. Flipick’s own platform supports SCORM, xAPI, video, animation and eBooks, and integrates with MS Teams, Zoom, Google Classroom, Articulate and LTI compliant tools, so if you are running Flipick LMS the handover is direct. If you are running something else, the package is built to industry standard and should load without special handling.
Test it on a real learner account before you announce it. Not an admin account, which sees a different view and often masks tracking problems.
What can go wrong
Sending the wrong version of the source. Everything downstream inherits it, and catching it at QA means redoing stage two.
Discovering at review that the source document was never actually approved. This happens more than anyone admits. A deck that has been used for three years is not the same as a deck that has been signed off.
Expecting the course to fix content that is wrong. Conversion faithfully reproduces what you sent. If the policy is out of date, you now have an out of date policy in an attractive new format, deployed to more people.
Adding scope at review. “While we’re here, can we also cover…” is the single most common cause of overrun, and it is worth agreeing up front that new scope becomes a second course rather than an extension of this one.
What it costs
Productised pricing, starting at ₹1,50,000 per course. Productised is the operative word: you are not commissioning a bespoke build with an estimate that moves, you are buying a defined output at a defined price.
Whether that is good value depends entirely on what you would otherwise spend, which is a calculation most L&D teams have never actually run for a single course.
A reasonable first test
Send one deck. Preferably a mid-importance compliance course with a real audience, not your crown jewel and not a throwaway.
Fifteen days later you will know whether the output meets your standard, and you will have a real cost and a real timeline to plan the rest of the backlog against. That is worth considerably more than another vendor evaluation meeting.