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Generative AI Consulting and Solutions
Aiven Consulting Group helps organizations move generative AI from interesting demos to everyday work. We pick the use cases worth doing, build them with your data and set the rules that keep results accurate and safe.
What generative AI consulting covers
Generative AI creates text, code, images and summaries from a prompt. Large language models can draft a reply, summarize a long document, answer questions from your own knowledge base or help a developer write code. The technology is widely available. The hard part is choosing where it helps, connecting it to the right information and making sure people can trust the output.
Our generative AI consulting covers that whole path: use case selection, build versus buy decisions, design and prototyping, connecting models to your data, review and quality checks, and the usage policy that tells people what they can and cannot do. When a use case needs to carry out several steps on its own, we take it further with AI agent development.
Common generative AI use cases
Customer service assistants
Drafting replies and answering common questions from approved knowledge, with a person handling anything sensitive.
Content generation pipelines
First drafts of proposals, product descriptions, reports and marketing copy in your voice, reviewed before they go out.
Document summarization
Turning long contracts, reports and meeting notes into short summaries with the key points and open questions.
Code assistance
Helping developers write, review and document code faster, inside clear rules on what code and data may be shared.
What a generative AI engagement delivers
Use case selection
A short list of generative AI use cases scored for value, risk and effort, with the first one agreed.
Build versus buy decision
Whether to use a tool you already own, buy a product or build on a model, based on your data and control needs.
Prototype and pilot
A working prototype tested with real users and real content, then a pilot with clear success measures.
Connection to your knowledge
Retrieval from your approved documents and systems, so answers rest on your information rather than guesswork.
Quality and review checks
Tests for accuracy, tone and safety, and the points where a person reviews the output before it is used.
Generative AI usage policy
Plain rules on approved tools, what data may be used and how output is checked, aligned with your AI governance.
A sample generative AI engagement
A typical generative AI implementation runs 8 to 16 weeks, with discovery, prototyping, pilot deployment and a scaling plan.
Weeks 1 to 3: Discover
Find and score use cases, review your data and tools, and agree on the first use case and its success measures.
Weeks 4 to 7: Prototype
Build a prototype on your own content, test it with the people who will use it and refine the prompts and sources.
Weeks 8 to 12: Pilot
Release to a pilot group with review steps in place, and track quality, adoption and time saved.
Weeks 13 to 16: Scale
Harden the solution, train users, set ownership and plan the next use cases.
Getting generative AI right in the enterprise
Generative AI is easy to try and hard to scale. Accuracy depends on the information the model can see, so most business use cases need the model connected to your approved documents rather than answering from memory. Cost and quality depend on picking the right model for each task. And adoption depends on people knowing which tools are approved, which is why unapproved use, often called shadow AI, is usually the first problem we help solve.
Our generative AI insights follow how enterprises are putting these tools to work, and the free AI prompt library is a practical way for teams to start using approved tools well.
How to get started
Every engagement with Aiven Consulting Group starts with a free 30-minute intro call on Zoom. We talk through your goals, where AI is used today and what is getting in the way. If there is a fit, a paid engagement begins with a strategy session that maps what your organization actually needs and produces an AI blueprint for the work ahead. Request your intro call.
Tools and examples for generative AI
Related services and reading
Generative AI consulting questions
What does a generative AI consultant do?
A generative AI consultant helps an organization choose where generative AI is worth using, decide whether to buy or build, connect models to the right information, test the output for quality and safety, and set the rules people follow when they use it.
How long does a generative AI implementation take?
A typical generative AI implementation with Aiven Consulting Group runs 8 to 16 weeks, covering discovery, prototyping, a pilot and a scaling plan.
Should we build our own generative AI tool or buy one?
It depends on your data, your systems and how much control you need. Many first use cases are best served by a tool you already own or can buy, with custom work reserved for uses that rely on your own knowledge or processes.
How do you keep generative AI output accurate?
By connecting the model to your approved documents, testing it against real examples, and placing a human review step wherever the output could cause harm if it were wrong.
How does an engagement with Aiven Consulting Group begin?
With a free 30-minute intro call on Zoom. If there is a fit, a paid engagement includes a strategy session that maps what your organization needs and produces an AI blueprint.
Where is Aiven Consulting Group based?
Aiven Consulting Group is an AI consulting firm based in Indianapolis that works with businesses across the United States. Intro calls take place on Zoom, so location is never a barrier.
Ready to put generative AI to work?
Request your intro call