Business and technology engagement models

Start with the engagement that produces the next useful decision

Scope and delivery effort change materially with workflow complexity, data access, integration depth, security, regulatory requirements, architecture, user scale, and production responsibilities. DigiScience provides a clear entry assessment and scopes implementation after discovery.

Start with a Solution Assessment Request an engagement discussion

Engagement options

Five practical ways to work with DigiScience

The seven services can be delivered through the engagement model that best matches the decision, scope, and operating maturity.

First five: INR 29K / USD 349

Assessment

DigiScience Solution Assessment

INR 49K/ USD 599 standard

One problem • seven business days • defined scope

For business owners, functional leaders, and technical leaders who need the right path before implementation.

One defined business or technology problem
Workflow, automation, AI, cloud, deployment, and modernization paths assessed as relevant
Recommendation, risks, dependencies, and implementation brief
Full paid fee credited to implementation signed within 60 days

View assessment terms

Proof

Focused AI Pilot

Scopedafter readiness and discovery

One workflow • defined users • controlled data

For validating business value, data feasibility, quality, architecture, governance, and adoption before scale.

Agreed pilot brief and success criteria
Controlled working proof
Security, evaluation, human review, and audit controls
Production scale recommendation

View pilot model

Department

Department AI Accelerator

Scopedprogramme

Multiple workflows • integrations • formal controls

For a business function moving from isolated proofs toward reusable capabilities and governed adoption.

Prioritized workflow portfolio
Reusable integration and knowledge patterns
Role-based access, evaluation, monitoring, and audit
Adoption, operating model, and roadmap

Discuss accelerator scope

Platform

Governed Enterprise AI Platform

Customprogramme

Enterprise, regulated, hybrid, or private requirements

For organizations establishing a secure shared foundation for assistants, RAG, models, agents, and AI product teams.

AI landing zone and reusable platform services
Identity, network, data, security, and environment controls
MLOps or LLMOps, observability, resilience, and FinOps
Governance, operations, documentation, and handover

Explore platform scope

Operate

Managed AI Governance & Operations

Monthlyservice scoped to operating responsibility

Governance cadence • monitoring • optimization

For production AI requiring ongoing evaluation, risk review, operational visibility, release governance, incident handling, and cost control.

Model, prompt, agent, and policy review cadence
Quality, safety, usage, latency, and cost monitoring
Release approvals, evidence, incidents, and improvement backlog
Executive and governance reporting

Discuss managed operations

What shapes implementation scope

Price follows delivery responsibility and risk

A written proposal defines scope, assumptions, exclusions, milestones, acceptance criteria, customer responsibilities, commercial terms, and change control.

Number and complexity of workflows

Data quality, classification, and access

Integration and environment complexity

Security, residency, and compliance controls

Availability, scale, and support expectations

Cloud, model, licence, and specialist capacity costs

Start with clarity, then scope the right implementation

Share the workflow, desired result, current environment, constraints, and timeline. DigiScience will recommend the most appropriate engagement model.

Discuss Your Problem