GenAI Engineering Services in Otago
Anyone can wire up an API call. Shipping a GenAI feature that's reliable, cost-aware and safe under real user load for a Otago business is a different job — that's what I do.
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- Transparent pricing
- No lock-in contracts
- Proven results
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Beyond the demo, for Otago teams
I build the evaluation harness, guardrails and monitoring alongside the feature itself, so quality doesn't silently regress after launch. Anyone can wire up an API call — shipping something reliable, cost-aware and safe under real user load from Otago is a different job.
What's included
Prompt and pipeline architecture
Structured prompt design, function calling and multi-step orchestration built to hold up under real Otago user traffic, not just a clean demo.
Architecture components
- Function calling and tool-use design
- Multi-step agent orchestration where genuinely needed
- Structured output validation
RAG systems
Retrieval-augmented generation built on vector databases, grounding responses in your Otago business's actual data instead of relying on model memory alone.
RAG components
- Document ingestion and chunking strategy
- Vector database selection and indexing
- Retrieval quality evaluation
Evaluation suites and guardrails
Automated evals and safety guardrails so quality is measured continuously for your Otago deployment, not just checked once before launch.
Cost-aware model routing
Model routing and caching that keeps inference costs sane as usage scales for Otago businesses.
How the engagement runs
Process
Scoping & architecture
We define the exact use case, failure modes and success metrics before writing a single prompt for your Otago product.
Build & evaluation
The feature and its evaluation harness are built together, not bolted on afterward.
Launch & monitoring
Production monitoring catches quality regressions in your Otago deployment before users do.
Who this is for
Product teams shipping AI features
Otago teams that need an AI feature to actually hold up in production, not just impress in a demo.
Engineering teams needing a specialist
Otago businesses that want a GenAI specialist to plug into an existing team rather than own the whole build.
Tools & technology
Model providers
LLM platforms
OpenAI, Anthropic (Claude), and open-source models via Together or self-hosted
Chosen per use case for your Otago deployment — cost, latency and quality all factor in.
Note
Vector databases and orchestration tooling are selected to fit your Otago team's existing stack wherever possible.
Quick answer
GenAI engineering here means building the full production system around a language model — prompt architecture, RAG retrieval, evaluation harness and guardrails — not just wiring up an API call. For a Otago business, that's the difference between an AI feature that looks good in a demo and one that stays reliable, cost-aware and safe once real users in Otago are hitting it every day.
How this compares to a no-code AI wrapper tool
- No-code AI wrappers give your Otago business a generic prompt box; this builds structured pipelines with function calling, multi-step orchestration and validated outputs tuned to your actual use case.
- Wrapper tools rarely ground answers in your own data; RAG systems here index your Otago business's actual documents in a vector database so responses aren't relying on model memory alone.
- No-code tools have no evaluation layer; this ships automated evals and safety guardrails so quality for your Otago deployment is measured continuously, not just eyeballed once.
- Wrapper tools bill per generic call with no cost controls; model routing and caching here keeps inference costs sane as usage scales for Otago businesses.
Why Otago teams choose Deepak Suhag
Production LLM pipelines, RAG systems and evals that hold up past the demo — built by someone who ships and monitors, not just prototypes.
How it works
Simple, transparent process — from first contact to measurable results.
Discovery Call
30-minute deep dive into your business, goals, and current marketing channels. No prep needed.
Strategy Blueprint
Full-funnel channel map, budget allocation, KPIs, and a 90-day growth roadmap.
Hands-on Execution
Campaign setup, conversion tracking, creative briefs, and continuous A/B testing.
Scale & Optimise
Weekly ROAS reports, budget reallocation, and monthly strategic reviews.
Tools & platforms
The exact stack I use daily across growth marketing, web development, AI, and automation — no guesswork, no vendor lock-in.
Why work with Deepak
Here's what makes this different from every other option in Otago.
Practitioner, not a consultant
I manage live campaigns daily — not just strategy decks. Your budget is treated like my own money.
Full-funnel accountability
From first click to closed deal. I track CAC, LTV, and ROAS — not just impressions or CTR.
AI & automation-first approach
I build marketing systems that scale without scaling headcount — using n8n, Make, and AI integrations.
No agency layers
No account managers, no junior execs. You work directly with me — every strategy call, every week.
Everything you need to know
Still have a question that isn't answered here? Reach out directly — I respond to every inquiry personally.
Ask a question01Which LLM providers do you work with for Otago clients?
OpenAI, Anthropic (Claude), and open-source models via providers like Together or self-hosted where it makes sense.
02Can you build RAG systems for Otago businesses?
Yes — retrieval-augmented generation with vector databases is a core part of the work.
03How do you handle hallucination risk?
Grounded retrieval, structured outputs, automated evals, and human-review checkpoints for anything customer-facing.
04Do you build the whole product or just the AI layer?
Either — I can own the full feature end-to-end, or plug into your existing Otago engineering team.
05What does a GenAI engineering engagement cost in Otago?
Cost depends on whether you need a single feature (prompt design plus RAG, for example) or a full evaluation and monitoring layer around an existing feature. Share what your Otago team is trying to ship for a specific quote.
06How is this different from hiring a general software agency for AI work in Otago?
A general agency in Otago can usually wire up an API call but rarely builds the evaluation harness, guardrails and cost-aware routing needed to keep quality from silently regressing after launch — that production-hardening layer is the core of this work.
07How long until a GenAI feature is production-ready for our Otago product?
A scoped feature with RAG and basic evals typically takes 3-6 weeks from architecture to launch, depending on how much of your Otago business's data needs to be ingested and indexed first.
08Is this a good fit if we just want to try an AI chatbot experiment in Otago?
For a quick, low-stakes internal experiment, a lighter no-code tool is often the faster and cheaper starting point. This is built for Otago teams shipping an AI feature to real customers, where reliability and cost control actually matter.
09What happens in the first week for a Otago engagement?
The first week defines the exact use case, likely failure modes, and success metrics for your Otago product before a single prompt gets written — so the evaluation criteria exist before the build does.
I've spent 10+ years managing campaigns across D2C, B2B, and SaaS — from small monthly budgets to large seven-figure spends. What I've learnt: most businesses don't need more ad spend. They need smarter systems. That's what I build.