Rapid MVP Development: Need to know an idea works on your real data before funding the full build?
We build a first version on your real data, measured every day, so you see what works before committing further. For Fleek, agents were drafting replies in the live queue about 10 days after the first call.
Thick documents and many meetings come before anyone sees software running on real data.
02
Demos that break on real data
A prototype looks good on sample data, then falls over on your real records.
03
Big-bang projects that didn't land
A large implementation was promised in one go, and it never quite worked.
What we build
How we get to a first version
A first version on real data
The software runs on your real cases from the start. Agents only draft, and your team compares their work with its own.
Success criteria agreed first
We agree what a correct outcome looks like and how we will measure it before we build.
One station first
Prove it where the pain is, then scale: at Bosch's Jaipur plant we started with a single station before taking it to whole lines.
A demo every sprint
Daily progress notes and a demo every sprint, so you see the product take shape.
Small, fixed-price steps
Each step can be quoted and delivered on its own, so budgets stay predictable.
Built to keep
The first version lives in your repository from the first commit and grows into the full system, rather than being thrown away.
Proof
Proof
A first version, fast
Support agents that draft the answer before a person opens the ticket
Fleek runs a B2B marketplace for second-hand wholesale clothing. Its support team was answering the same "where is my order?" questions by hand, across five tools.
We built agents that read each ticket, name its intent, look up the order and leave a ready-to-send reply inside Zendesk, the helpdesk Fleek already used. The agents never reply to a customer directly: every answer is a draft that a person approves.
Each kind of ticket has its own playbook, so the support team can change how a category is handled without waiting for a developer. Our engineer ran a hands-on AI master class for the team, so they could shape the playbooks themselves.
“The responses have become a lot more reliable … one click send. That's amazing.”
Fleek customer-experience team, daily sync, October 2025
Source: Fleek–Wisflux working sessions, October–November 2025
~10 days
from the first ideation call to agents drafting replies in the live queue
84–85%
of "where is my order" tickets classified correctly, checked against 50–100 tickets hand-labeled by Fleek's team
Our manufacturing work
Paperless, machine-connected assembly lines for Bosch's Jaipur plant
Bosch Limited's Jaipur plant builds fuel-injection pumps on high-mix lines, where every changeover used to mean paper lists, binders and memory. Since 2021 we have built the digital layer these lines run on: station screens with the right parts and checklists, links to the machines, and camera-based AI checks.
Station screens show the SAP-synced bill of materials, part images, drawings and setting values for the current variant, and setup checklists fill themselves in. Industrial cameras with AI models catch a missing retaining pin or a missing or reversed washer, and a part mix-up at the drive-shaft station, before the pump moves on.
We started with a single station to prove the idea, then took it to the whole line and on to other lines. Paper and digital ran side by side, and paper went only when the team trusted the screens.
Source: Bosch–Wisflux orders, correspondence and project records, 2021–2026
Since 2021
continuous work with the plant, each enhancement quoted and delivered on its own purchase order
DX Award
won in 2023 by the plant's Digital BoM programme, built with Wisflux
Sankalp
Bosch's 2026 supplier event, to which Wisflux was invited as one of a small group of long-standing, trusted companies
—ISO/IEC 27001:2022 and ISO 9001:2015, certified by TNV System Certification, valid to October 2028.
—GDPR-ready practices.
—Read-only access to your data first; write access only when it is earned.
—Background checks for engineers, secrets in a vault, anonymized data outside production, and on-premises deployment where required.
—You own everything: code in your repository from the first commit, running in your cloud or on your premises.
How we start
One workflow first. Real data, drafts first.
01
Workflow review call
Our founder, Chandraprakash Sharma, walks through one workflow with you and says plainly whether an agent can take it on, and if not, says that too. There is no charge for this call.
02
Agent pilot
One workflow, on your real data, drafts first, with success criteria agreed before we start. Your team compares the drafts with its own answers.
03
Roll out, one category at a time
We switch on the standard cases first and train the people who will use it. Hard cases stay with your team until it is confident, and every draft is still approved before it goes out.
We stay until it is used: a project ends when your team uses the system daily, not when it goes live. Every engagement is quoted to its scope.
You see the work as it happens: daily progress notes, a demo every sprint, and a work report behind every invoice showing where each hour went.
Other ways to work with us: a fixed-scope build with milestones, a dedicated team of named engineers, or run and support for systems we built or inherited.
Questions
Rapid MVP Development: common questions
How soon can we see something working?+
It depends on your data and systems, so we don't promise a date before we've seen them. For Fleek, agents were drafting replies in the live queue about 10 days after the first call.
Is the first version thrown away?+
No. It is built in your repository from the first commit and grows into the full system once it has proved itself.
How is it priced?+
Every engagement is quoted to its scope after a first conversation. A fixed-scope build has milestones, with buffers stated openly in the plan.
Are we locked in if it doesn't work out?+
No. You own everything from the first commit: the code lives in your repository and runs in your cloud or on your premises. If we part ways, you keep everything.
Who sees our data?+
We are ISO 27001 certified. We start with read-only access, use read replicas instead of production credentials, keep secrets in a vault, and can keep sensitive data on private, open-weight models.
We've already tried ChatGPT or Claude for this. What do you add?+
Many teams now try. The demo is easy; production is not: connecting your systems, measuring accuracy, keeping a person in the loop, handling the unusual cases and keeping it running. We build with the same AI tools, and we can teach your team as we go.
Start with the idea you most want to test.
Tell us what you'd build first if it only had to work on your real data. Tell us about one workflow. We'll walk through it with you and say plainly whether an agent can take it on — and if it can't, we'll say that too.
