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Custom AI development · India
Custom AI development for when your data is the edge
Webzenia builds custom models and RAG over your own documents, inside your product. We say so if off-the-shelf would do.
Get a free AI scoping call- 92%
- Answer accuracy on your own data
- 70%
- Manual review hours removed
- 8 weeks
- From data to a model in production
Trusted by ambitious brands worldwide, small and large
What custom AI development actually is
A model trained on your own data, not a thin wrapper over someone’s API
Most "AI development" rents a prompt on a hosted API: generic, leaking your data. Custom AI is trained on your data and owned by you.
Trained on your data
A model fine-tuned or built on your own history and documents, so it answers in your domain, not a generic one scraped off the web.
Deployed in your stack
Runs in your cloud or on your servers, inside your VPC, so customer data never leaves an environment you control.
Owned, not rented
The weights, the code and the pipeline are yours, so you are not held hostage to a per-call API price that moves without you.
What we build
The custom AI systems we train, fine-tune and ship
Not "do AI". The specific models and systems that earn their cost, each trained or tuned on your data.
Custom RAG & search
A retrieval system over your own contracts, policies and tickets, answering with citations, not a public chatbot’s guess
Output
sourced answers in seconds
RAGYour docs
Predictive models
Demand, churn and credit-risk models trained on your own history, scored on your own outcomes
Output
forecasts on your numbers, not a template
ForecastChurn
Fine-tuned LLMs
An open model fine-tuned on your data and your tone, so it answers in your domain and the weights stay in your account
Output
a model that is yours
Fine-tuneOwned
Document intelligence
Models that read invoices, KYC and contracts in your formats and regional languages, extracting fields straight into your systems
Output
manual keying gone
ExtractionMultilingual
Computer vision
Vision models trained on your line or field images for defect spotting, counting and verification
Output
inspection at machine speed
VisionQA
Agents & automation
AI agents that run a multi-step process end to end, wired into your CRM and tools on n8n and LangChain
Output
a workflow that runs itself
Agentsn8n
Why a trained model beats a thin API wrapper
A model you own, or an API you rent
Most "AI development" rents a prompt on a hosted API: your data leaves on every call, you own nothing. A model trained on your data flips that.
| API-wrapper AIA prompt over a rented model | Custom-trained AIWebzenia, your data and your weights | |
|---|---|---|
| Where your data goes | Sent to a third-party API on every single call. | Stays in your stack; the model is trained, then runs in your VPC. |
| How good the answers are | Generic; the same model everyone else is prompting. | Tuned on your domain, your data, your tone of voice. |
| The cost at volume | A per-call fee that scales straight up with usage. | A build cost, then cheap inference you control. |
| What you own | Nothing; remove the API key and it stops. | The weights, the code and the pipeline, in your name. |
| DPDP residency | Data processed wherever the vendor’s servers sit. | Runs and stores in India, designed to the DPDP Act. |
Are you building a model, or renting a prompt?
A wrapper is the right call for a quick experiment. For anything that handles your customer data at volume, the economics and the law point the other way. We train the model on your data, deploy it in your stack, and hand you the weights, so the system gets better as your data grows and the cost stays under your control.
How we build AI in India
Built for what an Indian business can run and own
An AI build scoped for a US cloud bill does not survive an Indian P&L. We build to your data, your rupees, and the law.
- 01of 04
Sending customer data to a foreign API on every call is exactly what the DPDP Act now governs.
We train and deploy on infrastructure you control, with consent, retention and processing kept inside India, so the model is compliant with the Digital Personal Data Protection Act before it scales, not retrofitted after a notice.
Our methodTrained and served in India, designed to the DPDP Act. - 02of 04
A per-call API is cheap at a thousand calls and brutal at a million.
We model the crossover before we build: a hosted API like OpenAI or Anthropic against an open model you fine-tune and run yourself, on cost per call, latency and residency, so the unit economics hold at your real volume.
Our methodBuild vs API crossover modelled on your real volume. - 03of 04
Most AI failures are data failures, not model failures.
We audit what data you actually hold and how clean it is before promising an outcome, because a model trained on a thin, messy dataset is a demo, not a system that ships.
Our methodData readiness checked before a model is scoped. - 04of 04
Your customers write in Hindi, Marathi and Tamil, not just English.
We fine-tune and test on Indian-language data, so document intelligence and support models read the scripts and code-switching your customers actually use, instead of failing on the first regional-language form.
Our methodFine-tuned and tested on Indian-language data.
What the engagement covers
From your data to a model in production, end to end
Not a notebook and a demo. The full pipeline: data, training, evaluation, deployment and monitoring.
Data pipeline & prep
Your data collected, cleaned, labelled and turned into a training set, with the gaps flagged honestly
Output
data a model can learn from
CleaningLabelling
Model training & fine-tuning
The model trained or fine-tuned on your data, with the architecture chosen for your task, not the most famous one
Output
a model fit to your problem
TrainingFine-tune
Evaluation & benchmarking
Measured against a target you set on real data, with accuracy, latency and edge cases reported plainly
Output
proof before production
BenchmarkMeasured
Deployment
The model served in your cloud or on your servers, behind an API your apps can call, inside your VPC
Output
a model live in your stack
Your VPCLive
Monitoring & retraining
Drift, accuracy and cost watched after launch, with retraining when the data moves under it
Output
a model that stays accurate
DriftRetrain
Handover & enablement
The weights, code and pipeline handed to you, and your team trained to run and retrain it
Output
a capability you keep, not a dependency on us
HandoverTraining
Industries we build AI for
Built for the data your industry actually holds
A lender's credit history, a factory's line images and a clinic's records are nothing alike. Train on the data you have.
BFSI & lending
Credit-risk and fraud models, DPDP-resident.
Retail & D2C
Demand forecasts and recommendation models.
Manufacturing
Vision QA and maintenance prediction.
Healthcare
Document intelligence and triage models.
Logistics
Routing, ETA and demand models on your data.
SaaS & tech
In-product AI features and fine-tuned copilots.
Our stack
Tools we use to build the model and app
The stack behind custom AI from model to production app.
OpenAI
Why OpenAI
OpenAI’s models are the fastest route to a capable AI feature, the right default when training from scratch isn’t justified.
How we excel
We start most builds on OpenAI with prompting and fine-tuning, so a custom feature ships in weeks, and we only train bespoke models when the data demands it.
CapabilitySpeed to shipFine-tune
OpenAIYes
AnthropicLimited
Open modelsYes
From scratchSlow
How the build runs
From your data to a model you can judge, in weeks
A custom AI build on a clear timeline, where a measured result lands before the production commitment.
Check the data, then scope the model
We audit what data you hold and how clean it is, model the build-versus-API economics at your volume, and scope the model and target. You sign off before training starts.
- Dataaudited
- Economicsmodelled
- Targetset
- Scopeapproved
Train on your data, prove it on a benchmark
We build the data pipeline, train or fine-tune the model on your data, and benchmark it against the target on real cases, so you judge the model on a number, not a demo.
- Pipelinebuilt
- Modeltrained
- Benchmarkmeasured
- Accuracyreported
Ship it to your stack, then keep it accurate
We deploy the model in your cloud, hand you the weights and code, and watch drift, accuracy and cost, retraining when the data moves under it.
- Deployedyour VPC
- Weightshanded over
- Driftwatched
- Retrainheld
Reported against a measured accuracy target, a real-data benchmark and a cost-per-call figure, not training hours.
Reported on the benchmark
TrainedBenchmarkedOwned
An insurance broker cuts lead response to 90 seconds with Webzenia.
Our commitment
Our commitment, in writing
Custom AI goes wrong when the model misses its target, when your data leaves your servers, or when the inference bill blindsides you. We commit against all three.
Benchmarked before deploy
We train and measure the model against a target you set on real data before anyone signs off production. No benchmark, no deploy.
You own the weights
The model weights, the code and the pipeline are in your accounts and your name. Leave us and the model still runs, with no API key holding it hostage.
Your data stays in India
Trained and served on infrastructure you control, designed to the DPDP Act, never sent to a foreign API on every call.
Costs on the table
Training and inference costs estimated up front, with the build-versus-API crossover modelled, so the unit economics are clear before you commit.
If the model does not hit the target, you do not deploy it.
FAQ · 07 questions
Custom AI development, answered.
Still weighing it up?
The first audit is free and produces a written, scoped estimate. No retainer pitch on the call.
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Accepting new clients · 2026
Could a custom model make your data the edge?
Tell us the problem and the data you sit on. We will tell you honestly whether a custom build, RAG over your documents, or an off-the-shelf model is the right call.
What happens next
- 1Send the briefThe problem and the data you hold
- 2We assess fitCustom build or off-the-shelf model
- 3We reply on WhatsAppAn honest read, no hard sell
Tell us what you need.