Put Large Language Models to Work in Your Product
Splicity connects your business to the leading generative AI APIs — GPT, Claude, and Gemini — and builds the logic, guardrails, and interfaces that make them production-ready. Clients leave with working AI features, not prototypes.
Model-agnostic expertise
We work across GPT, Claude, and Gemini so you get the right model for the job, not just the most popular one.
Cost-controlled deployment
Token budgeting, caching, and smart routing keep your monthly API spend predictable as usage grows.
Production-grade reliability
Every integration includes error handling, output validation, and logging so your AI feature holds up under real traffic.
Generative AI Integration
The outcome we're after
Most teams know they want AI in their product but stall on the same questions: which model fits their use case, how to keep outputs consistent, and how to avoid runaway API costs. The gap between an OpenAI playground demo and a reliable production feature is wider than it looks.
We assess your use case first — content generation, document analysis, customer-facing chat, internal automation — then choose the right model family and design the full integration: API calls, context management, prompt templates, fallback logic, and cost controls. We work directly with GPT-4o, Claude 3, and Gemini 1.5 APIs, not third-party wrappers.
The result is an AI feature that behaves predictably at scale, stays within budget, and is maintainable by your own team. Clients typically cut the manual time for their target task by 60 to 80 percent within the first quarter of deployment.
What we deliver
Key offerings
Why Splicity
Why teams choose us for this
A senior team, a fixed plan and long-term ownership — the things that decide whether a project actually succeeds.
One accountable team
Strategy, design, build and support handled end to end by senior people — not handed off and lost.
Fixed, transparent scope
A clear plan and estimate before any work begins. No open-ended billing, no surprises.
Built to scale & rank
Performance, security and SEO engineered in from day one — not bolted on at the end.
A long-term partner
We support, monitor and evolve what we build, so it keeps delivering value long after launch.
Our process
How we work
Discovery
We learn how you work, your goals and constraints.
Design & Build
We design the experience and engineer it to spec.
Test & QA
Automated and manual testing before anything ships.
Deploy
Smooth, low-risk releases on your infrastructure.
Maintain & Grow
Proactive support, optimisation and iteration.
FAQ
Frequently asked questions
Which AI model should we use — GPT, Claude, or Gemini?
It depends on your task, latency requirements, and cost ceiling. GPT-4o leads on broad reasoning, Claude 3 excels at long-context document work, and Gemini 1.5 is strong for multimodal inputs. We benchmark all three against your actual data before recommending one.
How do you stop the model from returning inaccurate or off-brand responses?
We combine structured prompt templates, retrieval-augmented generation (RAG) to ground answers in your verified content, and an output evaluation layer that flags or blocks responses outside defined parameters. This is standard in every integration we ship.
How long does a typical generative AI integration take?
A focused single-feature integration — such as a document summarizer or an AI-assisted search — generally takes four to eight weeks from scoping to production. More complex multi-model workflows or full product features are scoped after an initial discovery sprint.
Will we be dependent on Splicity to maintain the AI feature afterward?
No. We document every prompt template, pipeline configuration, and environment variable, and we hand over the codebase with a walkthrough session. Your developers can update prompts, swap models, or adjust cost controls without us.
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Ready to start your generative ai integration project?
Tell us what you're building. We'll scope it and come back with a clear plan, timeline and estimate.