AI and ML engineering assistant
Design LLM apps and agents, choose models and infrastructure, build evals, and ship ML systems -- grounded in your stack, data, and constraints.
Prova en av dessa
AI and ML engineering assistant turns Zeplik into a focused ai & ml engineering workspace. Design LLM apps and agents, choose models and infrastructure, build evals, and ship ML systems -- grounded in your stack, data, and constraints. Every answer is grounded only in the documents you provide, and the full Zeplik skill set stays available so you are never boxed in.
Upload or paste your material, describe the task in plain language, and the matching ai & ml engineering skill runs automatically to produce a structured, review-ready deliverable.
This is engineering guidance and draft code for your review, not tested, production-ready ML or LLM systems. Model, framework, and infrastructure choices depend on your data, scale, and constraints, so benchmark them against your own evals and load, verify every library version and API against current docs, and confirm safety, privacy, and cost behavior before you ship.
How to use AI & ML Engineering on Zeplik
Bring your material
Upload or paste the documents you are working from -- your source files or pasted text. Nothing is assumed; the analysis is built only from what you share.
Describe the task
Ask in plain language, for example "Design the architecture for a RAG app over the docs I'll describe -- retrieval, chunking, and the model call". Zeplik routes to the right ai & ml engineering skill without you naming it.
Review the deliverable
You get a structured, review-ready result with its working shown. This is engineering guidance and draft code for your review, not tested, production-ready ML or LLM systems. Model, framework, and infrastructure choices depend on your data, scale, and constraints, so benchmark them against your own evals and load, verify every library version and API against current docs, and confirm safety, privacy, and cost behavior before you ship.
Frequently asked questions
- Is AI and ML engineering assistant a substitute for a professional?
- No. This is engineering guidance and draft code for your review, not tested, production-ready ML or LLM systems. Model, framework, and infrastructure choices depend on your data, scale, and constraints, so benchmark them against your own evals and load, verify every library version and API against current docs, and confirm safety, privacy, and cost behavior before you ship.
- What do I need to provide?
- Your own documents -- your source files or pasted text. You can upload files or paste text directly into the chat; there is no account linking or connector to set up.
- Does it give me professional advice?
- It produces draft analysis and working papers for a qualified professional to review. It does not provide professional advice and does not replace one.
- Is it free to try?
- Yes. You can start for free and run these skills like any other Zeplik chat; credits only apply to normal model usage, with transparent pricing.
Skills in this workspace
- ML Engineer
- LLM App Patterns
- Autonomous Agent Patterns
- Agent Memory
- LLM Eval Harnesses
- LLM Observability
- Structured Generation
- Vector Databases
- LLM Serving
- LLM Quantization
- LLM Training Frameworks
- LLM Architectures
- Multimodal Models
- Voice Agents
- Voice AI Development
- Reinforcement Learning
- Interpretability
- AI Safety Guardrails
- Research Engineer
- ML Paper Writing
- Gemini CLI
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- InvestingAnalyze filings, model scenarios, and summarize positions. Live-data grounding is required before this vertical ships.
- Marketing & SEOWrite on-brand copy, plan campaigns, optimize conversion, and shape SEO and social strategy -- grounded in your product, audience, and inputs.
- SalesResearch accounts and prospects, write outreach, prep for calls, triage leads, and review pipeline -- grounded in the deal context you provide.
- SecurityReview code and architecture for vulnerabilities, model threats, harden auth and secrets, and plan incident response -- analysis for a qualified engineer to verify.
- Software DevelopmentDesign systems, review and debug code, plan tests, cut tech debt, and ship features -- grounded in the code and stack you share.
- Science & ResearchRun sourced research, check facts, synthesize literature, and set up scientific and computational analysis -- every claim traced to a source you can verify.
- DesignCritique and design interfaces, build design systems, audit accessibility, and write UX copy -- grounded in the screens, brand, and product you share.
- Data & AnalyticsExplore datasets, write SQL, run statistical analysis, build dashboards, and turn results into a story -- grounded in the data you provide.
- Product ManagementTurn ideas into specs, prioritize a roadmap, plan sprints, and review metrics -- grounded in the product context and constraints you share.
- HR & PeoplePlan hiring, design interviews, draft offers, run onboarding, and write reviews -- grounded in the roles, policies, and people data you provide.
- Customer SupportDraft replies, handle complaints, triage tickets, write knowledge-base articles, and read customer sentiment -- grounded in the ticket and account context you provide.
- OperationsDocument processes, write runbooks, plan capacity, assess risk, and brief leadership -- grounded in the systems, data, and context you provide.
- Career & Job SearchBuild a standout resume, tailor it to each role, prep for interviews, and negotiate the offer -- grounded in your real experience and the job you want.
- Game & Interactive DevDesign and build games, 3D web experiences, generative art, and programmatic video -- mechanics, engine code, and shaders, grounded in your project.
- Productivity & KnowledgeDesign Notion and Obsidian systems, organize files and notes, triage your backlog, and prep for deadlines -- built around how you actually work.
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