AI Consulting Services
Validate AI use cases, choose the right models, and define a realistic roadmap before investing in implementation
What our AI consulting services include
We map the business processes and product areas where AI or generative AI can bring measurable value, and openly mark where it is not worth the investment. You receive a prioritized list of use cases ranked by expected value and effort.
Each shortlisted use case is checked against data availability, model suitability, expected development and running costs, and technical constraints of your current systems. You learn which ideas are realistic to build now and which carry too much risk at this stage.
We define the data each use case needs and the model type that fits: an LLM-based generative solution or a classic ML model. We also help decide whether to build custom or use an existing tool, so you don’t overspend where a ready-made option works.
We turn the decisions into a step-by-step plan with priorities, stages, dependencies and rough budgets for each step. Your team knows what to build first, what can wait and what each stage should deliver before the next one begins.
We document the proposed architecture, key assumptions, model and data decisions, and our recommendations. Your in-house team or any development partner can pick up the plan and move forward without losing context or repeating the analysis from scratch.
Our Case Studies
A next-generation AI-powered trading platform that lets retail investors build, simulate, and run fully-automated ETF strategies.
We had to create a secure, real-time trading product from scratch, translate a complex vision into a clear roadmap, and keep development agile enough to absorb regular startup pivots.
Orion Protocol (ORN) is a decentralized blockchain platform leveraging open-source technology to aggregate liquidity from centralized and decentralized exchanges (CEXs and DEXs).
The primary aim of this project is to offer cryptocurrency traders and users optimal trading rates across various exchange markets and platforms.
Innovative SaaS solution that allows companies to accelerate payments from customers.
The Riabu software helps companies of all sizes – from big enterprises to small businesses – providing them with information about the past payment behavior of potential clients and merchants.
Poof app is a user-friendly and convenient mobile platform developed from scratch that offers a wide range of CBD products.
Thanks to outstanding user experience, product variety, and security, the Poof mobile app successfully catered to the evolving needs of both iOS and Android users and drove business results to the project owner.
Since 2017, our software creation team has consistently delivered industry-focused development services that get results.
How an AI consulting engagement works
Understand Business Goals & Context
We start with your business, not the technology: your objectives, current processes, constraints and how success will be measured. This keeps every AI decision tied to real business value from the first day, instead of chasing technology for its own sake.
Identify & Validate AI Use Cases
Together with your team, we collect AI ideas from different departments and score each one by business value, feasibility and expected impact. Weak ideas are filtered out at this stage, before they consume budget, and the strongest ones move on to deeper assessment.
Assess Data, Models & Risks
We check whether your data is ready for the chosen use cases, compare model options side by side and estimate development costs, running costs and technical risks. This is where unrealistic expectations get corrected, while changing direction still costs little.
Validate Assumptions (When Needed)
This step is optional. When a critical assumption is uncertain — for example, whether a model can handle your documents accurately — we run a lightweight experiment or proof of concept on your real data. We use it only when it reduces real risk, not by default.
Define a Clear AI Roadmap
All findings come together in a structured plan for implementation and later scaling. We walk your team through it, agree on priorities and define concrete next steps you can act on right away, whether you build with Peiko, your in-house team or another partner.
Why businesses choose Peiko for AI consulting
Fast and Safe AI Launches
We plan AI features to start with small working versions that reach real users quickly. After genuine feedback, the scope expands step by step. This shortens the path from idea to real usage and lets you see early whether the feature is worth growing.
Real Product Experience
We look at AI from product and business perspectives, not just performance metrics. Our AI Consulting is shaped by real product launches and user behavior. This helps avoid building technically impressive systems that do not create business value
Clear Communication Without Technical Overload
AI gets complex very fast. We explain decisions in plain language and keep trade-offs visible. So founders and product managers always understand what is being built and why. This reduces stress and surprise changes later
Efficient Use of AI Development Budget
We help you invest first in AI features that support validation and growth, and keep the scope realistic. Early budgets stay under control while assumptions are still uncertain, and clear results at each stage make further AI investment easier to justify internally.
Reliable Delivery and Scalable Architecture
We plan AI systems that can scale without constant rebuilding. With AI Consulting services, that means choosing models and infrastructure that support growth. It also reduces the risk of sudden performance drops when user numbers increase
Our AI Consulting Process


What Our Clients Say
We don’t just build software, we build success stories
We’ve earned a 100% Job Success score on Upwork as a result of consistent delivery, long-term client satisfaction, and predictable results.
View work historyOur work is rated 5.0 on Clutch, reflecting verified client reviews, strong professionalism, and a clear focus on scalable, business-driven digital solutions.
Read reviewsAI Consulting Services FAQ
AI consulting is right for your business if you’re considering AI or generative AI but aren’t sure where it pays off, what to build first or how much it will cost. It helps you avoid investing in the wrong use case. You’re likely ready if you have a clear business problem to solve, data related to that problem (even if it’s scattered or imperfect) and a budget for a pilot once the right use case is found.
Generative AI consulting services help you decide how to use large language models in your product or internal processes. We identify the most valuable use cases, such as AI assistants, knowledge search or content generation, choose the right model and approach (RAG, fine-tuning or a ready-made tool), estimate running costs per request and define data privacy and quality controls. When you’re ready to build, see our generative AI solutions.
The cost depends on the number of use cases we analyze, the depth of the data and technical assessment, and whether a proof of concept is needed to test critical assumptions. In our experience, an AI consulting engagement or feasibility study typically costs $500–$2,000, while a PoC is estimated separately. You can start with our free AI use-case identification to see where AI makes sense for you, or get a quick estimate with our cost calculator.
A typical AI consulting engagement takes 2–4 weeks. The exact timeline depends on the number of use cases, the complexity of your data and systems, and whether a proof of concept is needed. We define the timeline upfront, before the work starts, so you know when to expect the roadmap and recommendations.
No. Most companies come to AI consulting with scattered or imperfect data and no AI specialists on staff, and that’s exactly what consulting is for. We assess your data during the engagement and show what needs to be cleaned, collected or connected for each use case. You only need someone who knows the business processes and can give us access to the relevant systems and documents.
AI consulting answers what to build and why: which use cases are worth it, what data and models they need, what they will cost and in what order to implement them. The result is a validated plan. AI development is building that plan: training or configuring models, integrating AI into your product and supporting it in production. You can start with consulting and move to AI development services with the same team, or hand the plan to your own developers.