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The Readiness Assessment

A 5-day engagement that maps your data, surfaces high-ROI AI candidates, and recommends a pilot — fixed price.

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Case study
Tier-1 bank cuts reconciliation 92%

Agentic reconciliation across 14 source systems — six-week pilot, full rollout in one quarter.

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New
Private AI on dedicated GPUs

Frontier-class models on isolated infrastructure — your data never leaves the perimeter.

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Latest
Field notes: agentic eval at production scale

How we ship and operate eval harnesses for systems running ten-million-plus actions a month.

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Founder
Rohit Wakode — Founder & Director

B.Tech IIT Bombay · LLB GLC Mumbai. Building intelligent enterprise systems in India since 2014.

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Service · 02

Custom AI Engineering

Bespoke models, fine-tuning, evaluation harnesses, deployment pipelines.

When off-the-shelf models don't fit, we build the ones that do — fine-tuned, evaluated against your ground truth, and deployed to production. No research-project drift; every engagement targets a shippable system.

Evaluation is not an afterthought: we build the harness first, so quality is measured from day one.

FormatModels, fine-tuning, evals, deployment
TeamSenior ML + platform engineers
OutputA production AI system you own
Entry6-week pilot
01 — What's included

Bespoke AI, evaluated and shipped.

/ 01

Model selection & fine-tuning

The right open-weight or commercial base, tuned to your task.

/ 02

Evaluation harness

Ground-truth evals that gate quality before and after launch.

/ 03

Data pipelines

Training and feedback data pipelines that keep models fresh.

/ 04

Deployment

Production serving with observability and rollback.

/ 05

Guardrails

Validation, safety, and refusal calibration.

/ 06

Ownership

Code, weights, and runbooks transferred to your team.

02 — How we engage

From first call to production.

01

Define & evaluate

02

Build & tune

03

Deploy

04

Hand over

STEP 01

Define & evaluate

We agree the task and build the eval harness before training anything.

STEP 02

Build & tune

Select and fine-tune the model against your data and evals.

STEP 03

Deploy

Production serving with observability, guardrails, and rollback.

STEP 04

Hand over

Weights, code, and runbooks transferred — you own it.

03 — Where it pays

Use cases.

Fine-tuned domain modelsEvaluation harnessesModel deploymentData pipelinesGuardrails & safetyModel migration
04 — Engineering

Stack & standards.

Models
Open-weight + commercial
Fine-tuning / LoRA
Eval harness
Serving
vLLM / TensorRT
Observability
Rollback
Data
Training pipelines
Feedback loops
Versioning
05 — Outcomes

What good looks like.

Fits
Your task
Models built for your problem.
Measured
From day one
Eval harness gates quality.
Owned
By you
Weights, code, runbooks transferred.
06 — Questions

Answers, before you ask.

Do we own the model?
Yes — weights, code, and runbooks are transferred to you. No lock-in to us or a single vendor.
How do you prevent endless research?
Every engagement targets a shippable system with an eval threshold agreed up front — we ship when it clears, not when it's 'interesting'.
Open-weight or commercial?
Whichever fits your task, budget, and data-residency needs — we're model-agnostic.
Ready when you are

Let's talk about Custom AI Engineering.

Start with a fixed-price 5-day Readiness Assessment or a 6-week pilot. Senior engineers, measurable evals, and a system you own on handover.

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