Zero-to-production engineering
We take AI past the pilot and into fully working, securely integrated workflows your teams use every day.
Purposive AI Implementation Services
From pilot to production. Integrated, adopted, measured.
We design, build and run enterprise AI (agents, data pipelines and full solutions) and take it out of pilot purgatory into daily operations. Built in India, with the DPDP Act and CERT-In Directions designed in from day one.
- DPDP Act & Rules aligned
- CERT-In 6-hour reporting ready
- India data residency options
- Model-agnostic
Invoice matching · Rollout
IllustrativePilot Production
- Data pipeline Live
- CRM / ERP integration Connected
- Security guardrails Enforced
- Team enablement Trained
- Processing time −50% target
01 · Why it lands
Most AI stalls at the pilot.
Ours goes live.
Cross-industry playbooks
Ready-made compliance, data pipelines and security guardrails, tuned to the industries where AI pays back fastest.
Measurable return
Each milestone is tied to an operational KPI agreed up front, such as halving the time a process takes.
02 · Services
End-to-end implementation.
One accountable team.
From the first workshop to production support, we close the gap between what AI could do and what it delivers in your business.
Strategy 01
AI strategy & readiness
Use-case discovery, a value-ranked roadmap and an honest readiness check across data, skills, governance and compliance.
DPDP gap check included
Data 02
AI-ready data foundations
Pipelines, data quality and lineage that turn raw data into trusted inputs, with consent, purpose and retention tagged at the source.
Purpose & consent tagging
Prove 03
PoC to MVP
A proof of concept to test feasibility, then a minimum viable product that proves value with real users before you scale.
Outcome KPIs set up front
Agents 04
AI agent development
Purpose-built agents that work inside your systems, with role-based access, human approval steps and full action logs.
Human-in-the-loop by default
Build 05
Enterprise AI solutions
Custom AI applications integrated with your ERP, CRM, contact centre and messaging stack, engineered for security and scale.
Security reviewed before go-live
Run 06
AI Ops as a Service
Monitoring for accuracy, cost, drift and misuse, log retention, incident playbooks and steady improvement after launch.
CERT-In incident runbook
03 · What we do
Three disciplines.
One working system.
Data engineering
Clean, governed data the AI can rely on.
- 01 Scalable pipelines from your existing systems
- 02 Messy enterprise data cleaned and structured
- 03 Access, lineage and quality controls built in
04 · Compliance by design
India's data rules are live.
Your AI has to be ready.
Every AI system touches personal data and IT logs. Each rule below maps to something concrete we build into your system, so there is no separate project and no surprise rework.
6 hours
to report a listed cyber incident to CERT-In after noticing it.
CERT-In Directions, 2022
180 days
of logs for all ICT systems, kept within India.
CERT-In Directions, 2022
72 hours
to send a detailed personal-data breach report to the Data Protection Board.
DPDP Rules, 2025
1 year
minimum retention of processing logs and related data.
DPDP Rules, 2025
Full DPDP obligations apply in
— days · 13 May 2027
- 13 Nov 2025 Rules notified, Board set up
- 13 Nov 2026 Consent managers
- 13 May 2027 Notice, consent, rights and breach duties
Phased commencement of the Digital Personal Data Protection Rules, 2025. Dot marks today.
RequirementWhat we build into your AI
- DPDP
Notice and consent before processing personal data
Itemised notices and consent capture at every AI touchpoint, with consent and purpose stored alongside the data.
- DPDP
Reasonable security safeguards: encryption, masking, access control, monitoring, backups
Encryption in transit and at rest, PII masked before it reaches a model, role-based access, monitoring and backups.
- DPDP
Processing logs kept for at least one year
Tamper-evident AI activity logs of prompts, actions and access, retained to policy.
- DPDP
Breach: inform the Board and affected people without delay, detailed report within 72 hours
Breach detection, impact assessment and pre-drafted notices wired into the incident workflow.
- DPDP
Verifiable parental consent for children’s data
Age-gating and parental consent flows wherever an AI service may reach under-18 users.
- DPDP
Significant Data Fiduciaries: yearly impact assessment and audit, algorithmic risk checks
DPIA templates, model risk reviews and evidence packs ready for audit.
- DPDP
Data principal rights: access, correction, erasure, grievance
Request handling that finds and updates personal data across AI stores, including vector databases.
- CERT-In
Report listed cyber incidents within 6 hours of noticing them
24×7 alerting with a CERT-In reporting runbook and named owners.
- CERT-In
Enable logs for all ICT systems and keep them 180 days within India
Centralised logging for AI apps, APIs and agents, stored in Indian regions.
- CERT-In
Sync system clocks with NIC or NPL time servers
Time sync across the AI stack, so incident timelines line up.
- CERT-In
Designate a Point of Contact for CERT-In
Roles and contact details documented in your runbook.
This explains our delivery approach and is not legal advice. We work alongside your legal and compliance teams. Requirements are summarised from the sources at the foot of this page.
05 · How we deliver
Prove. Engineer. Integrate.
Then keep it working.
- 01 Prove
A focused proof of concept, then a minimum viable product on real data.
- 02 Engineer
Pipelines, models and agents built to production standard.
- 03 Integrate
Connected securely to your systems, with guardrails in place.
- 04 Adopt & run
Teams trained, performance monitored and improved after launch.
Data quality
Reliable inputs before anything goes live.
Responsible AI
Explainable, tested and governed from day one.
Outcome-led
KPIs set at the start and tracked to the end.
Secure by design
Enterprise security and compliance throughout.
06 · Capabilities
The right tool for the problem.
Not the newest one.
We stay model-agnostic and pick technology by fit, cost and risk.
- Generative AI
RAG, prompt design, fine-tuning and domain adaptation.
- Agentic workflows
Multi-step agents with tools, guardrails and approvals.
- Machine learning
Prediction, classification and anomaly detection.
- Language AI
Extraction, summarisation and search over unstructured text.
- Computer vision
Classification, detection and document OCR.
- Forecasting
Time-series models for demand, cash and capacity.
- Data engineering
Pipelines, quality checks, lineage and governance.
- MLOps & LLMOps
Versioning, evaluation, deployment and monitoring.
07 · Where we implement
Built for your sector.
And its rules.
Where AI helps
Banking, financial services & insurance
AI for document-heavy work, risk signals and better-informed decisions.
- KYC and loan document processing
- Claims triage and fraud signals
- Collections and customer service agents
- Advisor copilots grounded in policy documents
Built-in safeguards
- Customer financial data handled under DPDP consent and purpose limits
- An audit trail for every AI-assisted decision
- Sector regulators’ rules applied alongside DPDP and CERT-In
Front office to back office.
Wherever work repeats.
Marketing
Segmentation, campaign tuning and personalised journeys that respect consent and opt-outs.
Sales
Lead scoring, pipeline insight and guided selling.
Customer service
Case routing, agent assist and self-service across chat, voice and email.
08 · Why Purposive
Strategy, product and delivery.
Under one roof.
Founder-led delivery
Led by a founding team with nearly two decades of enterprise technology experience at Cisco. Senior people stay on your work.
India-first compliance
Based in Bengaluru. DPDP and CERT-In shape the architecture from the first sprint, not as an add-on.
We build our own AI products
We run AI products of our own, so we know what it takes to keep AI working in production, not just in a demo.
Outcomes, not hours
Every engagement is tied to agreed business KPIs (cost, speed, revenue or risk) and reported against them.
Model-agnostic
We choose models and platforms by fit, cost and data residency needs, and avoid lock-in where we can.
We stay after go-live
AI Ops as a Service keeps your systems accurate, monitored and audit-ready long after launch.
09 · FAQ
Common questions.
Our DPDP obligations start in May 2027. Why act now?
AI systems take time to design, test and roll out. Building notice, consent, retention and breach handling in now costs far less than rebuilding later. The core duties under the DPDP Rules, 2025 apply from 13 May 2027.
Do the CERT-In Directions already apply?
Yes. The Directions issued on 28 April 2022 have applied since 27 June 2022, including 6-hour incident reporting, 180-day log retention in India and clock sync with NIC or NPL time servers.
Can our data stay in India?
Yes. We design for data residency based on your needs and the rules that apply to you, including where models are hosted and where logs are kept.
How long does a first project take?
It depends on scope and data readiness. We agree the plan, milestones and success measures with you before any build starts.
Do you replace our legal or compliance team?
No. We build the technical controls; your legal and compliance teams own the decisions. We work with them from the start.
Move past the pilot
Put AI to work.
And prove it pays.
Tell us where your AI is stuck. We will show you the route to production on a call.
Sources: CERT-In Directions under Section 70B(6) of the IT Act, 28 April 2022. Digital Personal Data Protection Rules, 2025, notified 13 November 2025. Information current as of November 2026; not legal advice.