Fast-Track Your AI Innovation
Focused Build
The Rapid AI Pilot is a focused build of one prioritized use case with clearly defined success metrics, user workflows, and guardrails.
Validate & Scale
Designed to validate outcomes, confirm feasibility, and produce organization-ready learnings for scale.
Ideal Pilot Types
High-impact use cases perfect for rapid MVP development
AI Assistants & Chat Interfaces
Support, sales, or internal knowledge assistants with conversational capabilities.
Document AI
Parsing, classification, extraction, and summarization for contracts, KYC, and financials.
Predictive Analytics
Forecasting, propensity scoring, anomaly detection, and early warning systems.
Recommendation & Personalization
Content, products, next-best-action, and routing strategies.
4-Phase Pilot Plan
Structured approach to delivering your AI MVP in 2-4 weeks
Plan
Finalize scope, KPIs, data access, and user flows
Build
Implement data pipelines, models, retrieval/grounding, and interfaces
Validate
Run test sets, shadow or A/B tests, and error analysis
Launch
Deploy with monitoring, logging, cost tracking, and safeguards
Pilot Outcomes
Tangible deliverables that validate your AI investment
Working MVP
MVP with working UI/API, connected to real or staged data pipelines.
KPI Dashboard
Dashboard for accuracy, latency, cost, coverage, and adoption metrics.
Operational Runbook
Runbook with evaluation methods, safety controls, and rollback procedures.
Next-Step Plan
Next-step plan for optimization and scaling based on pilot learnings.
Success Metrics
Comprehensive measurement framework across business, technical, and compliance dimensions
Business KPIs
- • Time saved per process
- • Cost reduction achieved
- • Accuracy uplift measured
- • Conversion improvement
Technical KPIs
- • Response time (ms)
- • System throughput
- • Error rates (%)
- • Uptime reliability
Compliance & Safety
- • PII handling compliance
- • Hallucination controls
- • Safety event tracking
- • Audit trail coverage
Timeline
Weekly breakdown of pilot development
Week 1
Foundation & Setup
Scope lock, data hookup, baseline model configuration
Week 2–3
Development & Testing
MVP build, evaluations, and iterative improvement
Week 4
Launch & Measurement
Controlled launch with comprehensive measurement and documentation
What We Deliver
Complete package for immediate deployment and future scaling
Hosted MVP
API + lightweight UI (demo environment)
Source Code Repo
Well-documented, with deployment scripts
Test Suite
Sample tests to validate acceptance criteria
Integration Guide
Steps to connect to your systems (APIs, webhooks)
KPI Report
Baseline metrics + pilot performance
Handover Session
Code walkthrough and operational notes
Technical Stack
Recommended, flexible technology stack for rapid development
LLMs
OpenAI / Anthropic / Azure (or open-source Hugging Face models)
RAG & Vector DB
Pinecone / Weaviate / Supabase / FAISS
Orchestration
Node.js / FastAPI + Docker
Frontend
Minimal React or static HTML demo
Hosting
Vercel (frontend) + Render / AWS / GCP (backend)
Monitoring
Sentry + custom usage/cost dashboards
Client Responsibilities
Must-haves for successful pilot delivery
Data Access
Provide access to sample data (documents, product feed, images) and staging environment credentials.
Product Owner
Assign a product owner for weekly feedback and decision-making.
Timely Approvals
Timely approvals on scope & acceptance tests to maintain timeline.
Acceptance Criteria
Clear success criteria for pilot completion
MVP Deployment
MVP deployed to demo URL and accessible.
Core Workflows
Core workflows operate as defined in scope.
KPI Targets
KPI targets for pilot (agreed in SOW) either met or test results documented.
Handover Complete
Handover session completed and repo delivered.
Risks & Mitigations
Proactive risk management for smooth pilot delivery
Data Quality Issues
Risk: Incomplete or poor-quality training data affects model performance.
Mitigation: Use synthetic or sample datasets and include a data-cleaning sprint in the timeline.
Integration Delays
Risk: Complex system integrations could delay pilot delivery.
Mitigation: Use prebuilt connectors and keep integration minimal for pilot phase.
Cost Overruns on API Usage
Risk: Unexpected high API costs from model usage during testing.
Mitigation: Implement rate limits, caching, and batch processing from day one.
Add-ons & Next Steps
Scale your pilot into production-ready systems
Production Hardening
Security review, SOC2 readiness — priced separately.
ENTERPRISE READY
Full AI Ops
Complete onboarding with monthly retainer for ongoing operations.
MANAGED SERVICE
Feature Sprints
Additional feature development in 2-week increments.
AGILE EXPANSION
Frequently Asked Questions
Can this integrate with our CRM/ERP?
Yes—we provide integration blueprints and connectors for common enterprise systems.
What about vendor lock-in?
Designs are portable and cloud-agnostic; we document choices and alternatives for future flexibility.
What if the pilot underperforms?
We debrief and propose a remediation or alternative approach using the learnings from the pilot.
Complete AI Journey
From assessment to pilot to operations - your complete AI transformation path
Step 1: AI Readiness Audit
Start with a comprehensive assessment to identify your highest-ROI opportunities and create a strategic roadmap.
Learn about AI Readiness AuditStep 2: You Are Here
Transform your highest-priority use case into a working MVP in just 2-4 weeks with measurable KPIs.
Step 3: AI Operations & Scaling
Scale your successful pilot into a reliable, enterprise-grade system with comprehensive AI operations.
Explore AI Operations