Ship Generative Features Without the Production Surprises
Demos with one prompt are easy. Generative features that survive real users, real edge cases, and real spend are hard. We design, integrate, and harden generative AI into your product so it scales the day you launch.
Crafted by UnfoldCRO
The Problem
Generative AI Looks Magical in a Demo and Painful in Production
Hallucinations Reach Real Customers
A model that makes up product specs, refund terms, or compliance answers is worse than no AI at all. Most teams ship without a grounding strategy and find out at a customer's expense.
Costs Spiral the Moment Usage Grows
Without prompt caching, model routing, and per-feature budgets, a feature that costs cents at 100 users costs thousands at 10,000 users — and finance finds out before product does.
Latency That Breaks UX
10–20 second responses kill engagement. Streaming, request parallelization, and smaller-model fallbacks are the difference between a delight and an abandoned session.
PII and IP Leaks Into Third-Party Models
Most teams hand customer data to vendor models without a redaction layer or zero-retention contract. Legal finds out during the security review, not before.
A Production-Grade Generative Stack, Not a Wrapper
We design the orchestration, retrieval, evaluation, and observability layers that turn a model call into a product. Every integration ships with cost guardrails, eval coverage, and a fallback model so your roadmap never depends on a single vendor.
Multi-model orchestration with vendor-agnostic routing and graceful fallbacks
Retrieval grounding (RAG) over your documents, product catalog, or knowledge base
Streaming and function calling for sub-second perceived latency
Redaction, zero-retention contracts, and audit logs for every call
Eval harness with regression tests for every prompt change
Ready to Ship Generative AI That Survives Production?
Tell us the use case. We will tell you whether AI is the right tool, what the cost envelope looks like, and how long it really takes to ship.
What You Get
Your Production-Ready Generative AI Stack
Model Provider Integrations
Wired-up integrations with OpenAI, Anthropic, Gemini, and self-hosted open-source models with a single internal API surface.
Orchestration & Routing Layer
Smart routing that picks the cheapest model that meets the quality bar, with automatic fallback when a vendor is degraded.
Retrieval & Grounding Pipeline
Vector store, chunking strategy, and retrieval ranker so generated answers are grounded in your data — not the model's guess.
Cost & Latency Guardrails
Per-feature budgets, request quotas, prompt caching, and latency SLAs with alerting before you blow through them.
Eval & Regression Harness
Golden-set evals, LLM-as-judge scoring, and regression tests so a prompt change never silently degrades quality.
Observability & Audit Logs
Per-call traces, token accounting, and audit trails for compliance reviews and post-incident debugging.
How It Works
From Idea to Production in 6 Phases
Use-Case Discovery
We map the user job, the success metric, and the failure modes you cannot tolerate. Most projects shed half their proposed scope here — the half that should not have used AI in the first place.
Architecture & Provider Selection
We pick the model mix, retrieval design, and infrastructure (managed vs self-hosted) based on your latency, cost, and data-residency requirements.
Prompt & Eval Design
We build a golden test set before we write the prompt. Every iteration is scored, not vibes-checked. You see real quality numbers before launch.
Implementation & Hardening
Streaming responses, function calling, retrieval pipeline, redaction layer, cost guardrails, and observability shipped together — not as separate tickets.
Staged Rollout
Canary release behind a flag, watched on real traffic. Quality, latency, and spend dashboards are reviewed daily until rollout completes.
Operate & Iterate
Weekly eval runs, prompt regression coverage, and a backlog of cost-saving and quality-lifting moves so the feature gets cheaper and better every month.
Typical results
Results That Speak
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Projects Delivered
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Industries Served
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Faster First-Token Latency
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Lower Per-Request Cost
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Eval Coverage Before Launch
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Model Vendors Supported
What Our Clients Say
Testimonials
Rajkumar Venkatachalam
E-Commerce Expert | Conversion & Retention Strategist | Co-Founder of Neidhal.Com, Neidhal.Com
Abhijith Shetty
Founder, Gubbachhi | MICAn | Digit Insurance, McCann, Dentsu, Lowe Lintas, Leo Burnett, Tech Mahindra, Gubbachhi
Surbhi Sarda
SEO Strategist | Guiding Brands for Local & AI Search Ready
Nikita Sharma
Founder | Guide Businesses in Brand Perception & Digital Experience, ICraftAds
Ajay Binani
AI Automation Systems Learner | Author & Speaker on Minimalism, Get You At
Samriddhi Nagdev
Founder - Artcetra Design Studio | Brand Identity Designer, Artcetra Design Studio
The Difference
Why UnfoldCRO?
Vendor-Agnostic By Default
We do not sell you on one model provider. We design for portability so a price hike or rate-limit at one vendor never holds your roadmap hostage.
Evals Before Prompts
We refuse to ship without a regression harness. You get measurable quality numbers, not screenshots from one good demo.
Cost Guardrails Day One
Per-feature budgets, prompt caching, and request quotas land with the first version. No surprise invoices in week three.
Privacy & Compliance Built In
Redaction layers, zero-retention contracts, and audit trails. Security review becomes a checklist, not a re-architecture.
Frequently Asked Questions
Ready to Get Started?
Book a discovery call. We will scope the integration, propose a model mix, and ship a working prototype in 2 to 3 weeks.