Customer questions
Teams repeatedly explain delivery terms and product specifications.
Draft answers from approved catalog information and hand complex questions to staff.
Use AI to prepare customer responses, organize product information and summarize service enquiries. Ground the output in your catalog and store policies.
Start with repeatable operations that have usable source data and a clear way to check the result.
Teams repeatedly explain delivery terms and product specifications.
Draft answers from approved catalog information and hand complex questions to staff.
Supplier information arrives in price lists, tables and attachments.
Extract attributes and draft product descriptions for editorial review.
Complaints and return reasons are difficult to compare at scale.
Classify enquiries and prepare summaries for your customer service team.
AI prepares the output. Access rules, review steps and escalation paths are defined before launch.
The architecture depends on your data, workload, languages and hosting requirements.
RAG and BGE-M3 semantic search retrieve relevant passages from your knowledge base. Source references let employees check the information behind an answer.
We evaluate retrieval and answer quality using a reference set of questions. Requests with insufficient evidence are passed to staff.
Our stack includes Qwen 3, Gemma, Mistral Small and DeepSeek-R1. We evaluate models against your use case and scope adaptation or fine-tuning when the data supports it.
Process documents and spreadsheets and extract information from scans and images. GigaAM supports Russian speech workflows; speech recognition for other languages is selected and tested separately.
AI agents prepare documents, tasks, notifications and approval steps. Actions with business consequences follow agreed rules and require approval where specified.
We assess integration with your ERP, CRM, e-commerce platforms, product APIs, email and telephony.
Discovery covers available interfaces, data fields and read/write permissions. If an API is unavailable, we agree a file exchange or another integration method before estimating the project.
Deploy on agreed infrastructure: dedicated servers, virtual machines or containers. We agree hosting locations, data flows and processing arrangements with your IT team before any project data is transferred.
Role-based permissions, Active Directory, VLANs, VPNs and isolated environments.
Activity logs, backups, restore checks and availability monitoring.
Answer evaluation, model error reviews, knowledge base updates and a user support channel.
Prices, stock and order status come from connected systems. When current information is unavailable, the assistant passes the request to a member of staff.
Establish a baseline, then compare it with the pilot. The number of generated answers alone does not demonstrate savings.
Compare the existing process and AI-assisted work on a representative set of equivalent tasks.
Compare the existing process and AI-assisted work on a representative set of equivalent tasks.
Compare the existing process and AI-assisted work on a representative set of equivalent tasks.
You receive the architecture, integration documentation and operating procedures needed to run the solution.
Choose the process, source materials and acceptance criteria.
Agree hosting, integrations, cost and delivery scope.
Configure the solution and review quality with your team.
Train users, hand over documentation and support the system.
A possible starting point: A product and delivery assistant for one catalog category.
Scope, timing and budget follow an assessment of your workflow and data.
georgia@dinesco.com ↗+995 595 245 159