Fixed-price engagements. Real outcomes.

Step by step: from readiness assessment to production AI running live. Each engagement is priced, scoped, and delivered.

Service Model

Every engagement starts with the audit.

The Engagement Ladder: Step 1 AI-Readiness Audit, Step 2 Data Foundation Sprint, Step 3 AI System Build, Step 4 Managed AI-Ops

No hourly billing. Fixed scope, fixed price. Start with a 2–3 week audit that gives you a roadmap, then move up the ladder at your pace.

The Engagement Ladder

1

AI-Readiness Audit

Timeline

2–3 weeks

Pricing

Starting at ₹2–4L / $2.5K–5K

Assess your data governance, compliance posture, and AI readiness. Walk out with a report, risk map, and prioritized roadmap.

Deliverables

  • Data inventory & quality audit
  • Governance & compliance gap analysis
  • AI readiness scorecard
  • Risk & prioritized roadmap
  • Stakeholder workshop

Who this is for

Good for: New to data governance. Compliance teams. Boards asking 'are we ready for AI?'

What happens next

Book a 30-min scoping call. We'll ask about your systems, compliance requirements, and scope the audit.

2

Data Foundation Sprint

Timeline

8–12 weeks

Pricing

Starting at ₹10–20L / $12K–25K

Build a governed data foundation. Reconciliation, reporting pipelines, customer-360 with lineage. Production-ready from day one.

Deliverables

  • Cloud data warehouse setup
  • ETL/ELT pipelines (core systems)
  • Data quality & lineage
  • Governance layer (roles, policies)
  • Handoff & team training

Who this is for

Good for: Reconciliation chaos. Regulatory reporting pain. Ready to build on a clean base.

What happens next

We scope the 'core systems' together. Then sprint: design → build → test → handoff.

3

AI System Build

Timeline

Varies (by scope)

Pricing

Per outcome, fixed (typically ₹5–15L / $6K–18K per capability)

Production AI built on your governed foundation. RAG systems, agents, classifiers — priced per capability, not hours.

Deliverables

  • Requirement-to-architecture design
  • Data pipelines for model training
  • Model development & evaluation
  • API & production deployment
  • Monitoring & feedback loops

Who this is for

Good for: POC ready to scale. Specific AI use case (lending, operations, customer service).

What happens next

We define the capability. You agree on the price. We deliver to your acceptance criteria.

4

Managed AI-Ops

Timeline

Ongoing

Pricing

Starting at ₹1.5L / $2K per month

We run it. Monitor, retrain, improve. Keep AI performance in bounds. You focus on business.

Deliverables

  • Model monitoring & alerting
  • Monthly performance reports
  • Data drift detection & retraining
  • Performance optimization
  • Incident response

Who this is for

Good for: Production AI systems. Need operational bandwidth but not headcount.

What happens next

We baseline your system. Then we're on retainer — you get monthly cadence, guaranteed SLAs.

Common Questions

Everything you need to know about how we work.

Accepting new projects

Ready to make your
data AI-ready?

Let's discuss how we can build trusted data foundations for your AI. Book a free data-readiness call with our team today.

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Flexible Engagement