Will our data be used to train public models?

No. We use enterprise API tiers with zero data retention or self-hosted models, and sensitive fields are redacted before any prompt leaves your infrastructure.

How do you control AI running costs?

We cache embeddings and frequent answers, route simple requests to smaller models, enforce per-user quotas and report cost per request on a dashboard so finance can forecast spend.

Who owns the source code and IP?

You do. All source code, designs and documentation are assigned to you on payment of each milestone, and the repository lives in your organisation from day one.

How long does delivery take, and what does it cost?

Every scoped release is planned for delivery within 1–4 weeks, and larger scopes are planned to fit that window rather than stretching the schedule. A fixed quotation follows a free 30-minute scoping call.

Can we negotiate pricing for a long-term engagement?

Yes. Commitments of 3–5 months earn 5% off, 6–11 months 10% off, and 12 months or more 15% off with a 12-month rate lock and a dedicated delivery lead. Invoices are monthly in advance, scaling down or exiting needs 30 days’ written notice, and discounts are recalculated if a commitment is shortened. Everything is negotiable before signing.

How do you handle security and confidentiality?

Every engagement starts with a mutual NDA. Engineers work on managed devices with SSO and MFA, secrets never leave your vault, and production access is granted per person with audit logging.

Avg. support response 9.8h Verified authors · Razorpay secured

contact@dev3.tech +91 98776 58521

DEV3Technologies

Production AI, not demos

AI Implementation

RAG pipelines, document intelligence, AI agents and copilots integrated into your systems with evaluation, guardrails and cost controls.

Retrieval-augmented generation over your data
Document OCR & verification pipelines
Agentic workflows with human review
Evaluation harnesses, guardrails & cost monitoring

Delivery window

1–4 weeks per scoped release

Team

Senior, in-house squad

Ownership

Code & IP assigned to you

GeminiOpenAIClaudeLangChainPythonFastAPIpgvectorMongoDB Atlas Search

Value proposition

Why teams choose DEV3 for AI Implementation

We take AI from prototype to production: retrieval-augmented assistants grounded in your data, document intelligence pipelines and agentic workflows with human approval at the right checkpoints. Every system ships with an evaluation harness, guardrails and per-request cost tracking.

We are model-agnostic — Gemini, OpenAI, Claude or open-weight models — and design for data residency, PII redaction and auditability from the first sprint.

Engagement frameworks

Three ways to work with us

Full comparison →

Fixed Price

A defined scope, timeline and price agreed upfront, with milestone-based payments and change requests handled through a transparent impact assessment.

From $4,000 per project

Dedicated Team

A cross-functional squad that works exclusively on your product, follows your rituals and scales up or down with one month’s notice.

From $1,600 per engineer-month

Time & Materials

Pay for the hours worked against an evolving backlog, with weekly timesheets, sprint reviews and a budget cap you control.

From $10 per hour

Long-term partnerships — negotiable

Committing to a longer engagement lowers your rate. Every term below is a starting point we negotiate with you, in writing, before work begins.

Discuss long-term pricing

Commitment	Discount	Also included
3–5 month commitment	5% off	Applied to every monthly invoice in the committed period
6–11 month commitment	10% off	Quarterly roadmap reviews with your delivery lead
12+ month commitment	15% off	Rate locked for 12 months and a dedicated delivery lead

Conditions

Monthly invoicing, billed in advance
A minimum commitment term is agreed in the order form
30 days’ written notice to scale down or exit
Discounts apply to the committed period only and are recalculated if the commitment is shortened
Milestone acceptance within 5 business days of delivery
IP transfers to you on full payment
Price revisions only at renewal

Architecture roadmap

How the engagement runs, stage by stage

Discovery → UI/UX prototyping → systems architecture → engineering → QA → deployment. Select a stage for its deliverables.

Stage 1 of 6

Discovery & scoping

Stakeholder workshops, success metrics, constraints and a prioritised backlog with acceptance criteria.

Typical duration: 3–5 days

Deliverables

Use-case value & feasibility matrix
Data source audit
Success metrics and evaluation set

Case studies

Related engagements

All case studies →

StartupXYZ · Fintech · India

AI document verification that clears 85% of onboarding automatically

A Gemini vision pipeline extracts and cross-checks identity documents, scores authenticity in code and routes only uncertain cases to human reviewers.

Applications needing manual review

100%15%

Median verification time

1,560 min4 min

Gemini Python Node.js MongoDB Distributed Queue AWS

FAQ