How do you determine whether AI is actually the right tool for our problem?

We evaluate your use case based on data availability, error tolerance, and business ROI. If deterministic code, simple heuristics, or fixing existing data pipelines solves the issue more reliably and cheaply, we tell you straight rather than recommending unnecessary AI.

How does Sodiac evaluate which foundation model or LLM stack to adopt?

We evaluate open-weight models (Llama, Mistral) against closed API providers (Anthropic Claude, OpenAI, Google Gemini) based on inference cost, latency, data privacy constraints, and fine-tuning potential, recommending the stack that maximizes performance per dollar.

What does a typical AI consulting engagement look like?

Engagements typically start with a 2-week Discovery & Feasibility Sprint where we evaluate data readiness, build a proof-of-concept prototype, and deliver an actionable technical architecture and production roadmap.

Do you help with AI governance and DPDP compliance?

Yes. We design governance frameworks, data redaction pipelines, audit trails, and human-in-the-loop protocols ensuring your AI implementations comply with India’s DPDP Act and international data privacy regulations.

Back to Services

Consulting for teams adopting AI the right way

Strategy, architecture, and delivery for product development and automation — from a team that builds, not just advises. Responsible AI, honest advice, real results.

Consulting that ends in working software

Strategy & Roadmap

We help you find the AI use cases worth doing — the ones with real ROI — and sequence them into a roadmap your team can actually ship.

Architecture & Delivery

Not just slides. We design the architecture and build the first working version alongside your team, with responsible-AI guardrails from day one.

Team Enablement

We leave your team stronger than we found it — patterns, tooling, and hands-on enablement so you own what we build together.

How we engage

Assess

Understand your goals, data, and constraints — and where AI genuinely helps versus where it does not.

Prioritise

Score use cases by impact and effort, then agree on a focused, honest roadmap.

Prototype

Build a working proof of concept fast, so decisions are based on evidence, not hype.

Deliver

Harden the winner into production with governance, monitoring, and human-in-the-loop controls.

Enable

Hand over patterns, docs, and training so your team can extend it without us.

Where we help

AI Strategy

Use-case Discovery

Responsible AI

Data Readiness

Solution Architecture

Automation Design

MLOps & Deployment

Team Training

Why teams bring us in

Clarity on where AI actually pays off

Advice from people who ship, not just slide decks

Responsible-AI guardrails built in from the start

Faster path from idea to working prototype

Vendor-neutral, honest recommendations

Knowledge transfer so your team owns it

Right-sized for startups and lean teams

A partner for the build, not just the plan

Ready to build once the plan is set?

Product Development →AI Automation →For Startups →Our Responsible-AI approach →

1. Engagement Objective

2-Week AI Feasibility Sprint

Use-case prioritization, data readiness audit, and ROI modeling.

2 weeks

Architecture & Vendor PoC

Working prototype build, open-vs-closed model benchmarks, and tech spec.

+2 weeks

Enterprise Strategy & Governance

Complete enterprise AI roadmap, DPDP compliance review, risk controls.

+3 weeks

2. Deliverable Format

Executive Blueprint & Roadmap

Architecture diagrams, cost projections, risk matrix, and build plan.

Standard

Working PoC Prototype

Interactive prototype validating core hypothesis with your sample data.

+1.5 weeks

Production Technical Spec

Full API contracts, database schemas, and implementation backlog.

+1 week

3. Engineering Involvement

Bi-Weekly Advisory Sessions

Structured advisory reviews and architectural feedback with team.

Advisory mode

Embedded Principal Architect

Hands-on architectural guidance embedded with your tech leads.

+1 week

2–4 Weeks (2 Sprints)~30-35% AI Acceleration Savings

Estimated Investment (Sodiac AI-Accelerated)

₹1.5L – ₹2.4Ltotal

Traditional agency benchmark: ₹2.2L – ₹3.6L

Save ~32%

Agile 2-Week Sprint Roadmap2–4 wks to launch

Sprint 1

Architecture & Foundation

Scoping requirements, data connectors, and core architecture for ai & product consulting.

Sprint 2

Core Implementation & Logic

Building primary workflows: 2-Week AI Feasibility Sprint and Executive Blueprint & Roadmap.

Schedule a Consultation

100% Client Code & IP Ownership from Day 1

Direct senior engineer communication, no middle layers

Fixed sprint commitments with zero surprise fees

AI Consulting Questions Answered

Want honest advice on where AI genuinely fits your company? Request an AI advisory session →

We evaluate your use case based on data availability, error tolerance, and business ROI. If deterministic code, simple heuristics, or fixing existing data pipelines solves the issue more reliably and cheaply, we tell you straight rather than recommending unnecessary AI.
We evaluate open-weight models (Llama, Mistral) against closed API providers (Anthropic Claude, OpenAI, Google Gemini) based on inference cost, latency, data privacy constraints, and fine-tuning potential, recommending the stack that maximizes performance per dollar.
Engagements typically start with a 2-week Discovery & Feasibility Sprint where we evaluate data readiness, build a proof-of-concept prototype, and deliver an actionable technical architecture and production roadmap.
Yes. We design governance frameworks, data redaction pipelines, audit trails, and human-in-the-loop protocols ensuring your AI implementations comply with India’s DPDP Act and international data privacy regulations.

Talk to a consultant

Tell us what you are trying to do with AI. We will tell you honestly what is worth doing — and help you do it.

Talk to a consultant →