Decision service · India public-service AI

Define the human decision and evidence boundary for one India AI workflow before release.

This prospective LangData engagement reviews one public-service or regulated workflow in which AI may classify, retrieve, extract, route, summarize, or assist. It makes source and API permissions, task segments, Indian-language and channel evaluation, human authority, correction or appeal, degraded operation, and release evidence explicit. Digital India, IndiaAI, and Bhashini are cited as official public context only; no participation, certification, access, or customer relationship is implied.

Market: India Review: Human-decision, source/API, and evaluation review Prospective offer

Discuss the India AI review

Buyer and trigger

Who needs this decision review?

This page describes a prospective bounded offer. It is not customer proof or a claim that a market has requested the engagement.

Named buyer roles

Public-service product director
Department or regulated-enterprise technology lead
Responsible AI and evaluation lead
Grievance, appeal, or case-operations owner

Engagement trigger

A team is considering an AI-assisted workflow for real users or operators, but source permissions, API behavior, task-level evaluation, human decision rights, correction routes, and release evidence are too ambiguous for accountable approval.

Decision questions

Questions the engagement must answer.

Which task may AI assist, what output may it produce, and which decision must remain with an authorized person?
Which records, documents, APIs, user attributes, language inputs, and derived data are permitted for each task segment?
How should evaluation separate language, script, channel, user context, document type, source quality, and consequence rather than report one aggregate score?
When must an operator review, correct, override, escalate, or decline an AI output?
How can a user or operator challenge, correct, or route a disputed result without depending on the same failing path?
What evidence is required for release, constrained use, hold, degraded mode, rollback, and later model, prompt, source, or API change?

Concrete artifacts

What the decision pack includes.

The final scope, selected workflow, authorized source and API inputs, evaluation segments, customer decision roles, artifacts, specialist reviews, and acceptance process are agreed in a statement of work before the engagement begins.

Task and decision-rights specification

Permitted AI assistance, prohibited autonomous action, human decision authority, intended users, consequence tiers, escalation paths, and adjacent tasks excluded from review.

Source, API, and data-handling register

Authorized documents, records, APIs, identities, owners, purpose assumptions, access paths, derived data, retention inputs, and unresolved privacy or sector questions.

Language and channel evaluation matrix

Customer-selected languages, scripts, channels, user contexts, task variants, error categories, reviewer qualifications, acceptance decisions, and known coverage gaps.

Human review and appeal blueprint

Review queues, authority limits, correction and override paths, disputed-result handling, escalation records, feedback separation, and accountable case ownership.

Failure and degraded-mode catalogue

Unavailable API, stale source, language mismatch, low-confidence output, unsafe tool call, missing reviewer, and audit-gap scenarios with proposed hold or fallback decisions.

Pre-release evidence index

A traceable index of customer inputs, evaluation results to be produced later, control evidence, unresolved specialist decisions, release gates, and change-review requirements.

Boundaries

Outside this offer.

Model training, Bhashini integration, data labeling, API development, production release, hosting, or AI service operation
A DPDP, legal, privacy, security, procurement, records, accessibility, language-quality, or sector compliance opinion
A government-wide AI platform architecture or evaluation of workflows outside the selected boundary
Any claim of Digital India, IndiaAI, Bhashini, MeitY, or Government of India participation, approval, access, certification, local contract, customer proof, or result

Acceptance

How the review can be accepted.

Acceptance applies to the review artifacts and their traceability, not to an unperformed implementation or future outcome.

The accountable product owner confirms the selected task, permitted assistance, prohibited action, human decision authority, and correction or appeal owner.
Every source and API is authorized, excluded, or labeled unresolved, with ownership and purpose assumptions visible for customer specialist review.
The evaluation matrix separates task, language, script, channel, user, document, and consequence segments and reports no quality result before tests occur.
Human review, override, escalation, disputed-result, degraded-mode, and rollback decisions each identify a customer owner and required evidence.
The evidence index separates official public context, customer facts, LangData proposals, future test results, and qualified legal or policy decisions.

Accountable delivery role

LangData Public-Service AI Architecture Lead

This is an accountable LangData delivery role, not a named-person claim. Customer decision owners and specialist reviewers are identified in the agreed engagement scope.

Commercial evidence boundary

What public context cannot prove.

Official India sources establish public digital, AI, and language-technology programme context. They do not establish customer demand, LangData participation or access, Government of India approval, procurement status, certification, legal compliance, Bhashini integration rights, language coverage or quality, benchmark results, savings, release timing, or outcomes.

Annotated official sources

Public context, with explicit limits.

These official HTTPS sources support only the context stated below. Each boundary is part of the page's visible evidence record.

Digital India

Supports: Official Government of India and MeitY programme context for public digital-service transformation.
Boundary: Programme context does not prescribe this AI architecture, establish a customer requirement, or imply LangData affiliation, access, participation, or approval.

IndiaAI

Supports: Official national AI portal and IndiaAI Mission context for responsible discussion of AI initiatives in India.
Boundary: The portal does not establish that LangData participates in IndiaAI, is eligible to supply government work, or has delivered a public AI system.

Bhashini

Supports: Official Indian-language technology platform context that motivates language, script, channel, and task-specific evaluation questions.
Boundary: Bhashini's existence does not prove access, integration rights, language coverage, customer fitness, output quality, endorsement, or a LangData relationship.

Related LangData pages

Prospective engagement

Bring one India AI workflow and the human decision it must not obscure.

Name the task, permitted sources, language and channel segments, review owner, and release question. LangData can discuss a bounded prospective architecture review.