Generative AI Solutions
Practical Generative AI for Business
We focus on the business problem first and the model second. From content generation and summarization to conversational experiences and multimodal applications, we put GenAI where it can save time, improve decisions, or make information easier to use.
Transform generative AI into real-world business use cases, not just another feature.
— JBAS AI Engineering Team, JB Arrowstar Solutions
Generative AI for Business Purposes – JBAS
Whereas most discussions on GenAI begin with the tool itself, our discussion starts with the problem. At JB Arrowstar Solutions, we consider how you lose productivity in the workflow of your team due to excessive unstructured information, decision delays caused by the lack of sufficient information, or even a situation when a customer or employee cannot find the needed information quickly. Then we consider if it makes sense to use generative AI to solve the problem.
We develop it accordingly with content generation, summarization, conversational interface, intelligent search, recommendations, and multimodal applications, customized for your needs.
What We Build
1. AI Writing & Text Creation
Automatic writing of marketing copy, product descriptions, reports, and other types of repetitive text according to your style.
2. Text Summarization & Transformation
Conversion of lengthy documents, minutes of meetings, tickets of support, reports, etc. into an exact format where there are a summary, table, and list of actions without the need to search for three facts in a forty-page document.
3. Intelligent Search
AI-powered search that understands meaning and intention, not only key words, and will give you an answer to a question “What is our policy on refund of damaged goods” even if the phrase is not in the document at all.
4. Conversational AI
Text-based or voice chatbots, which have context throughout whole conversation and can make follow-ups questions like people do.
5. AI Recommendations
Recommendations for products, content, or actions based on actual usage data and business data are provided at the right time and in context, rather than as an afterthought.
6. Multimodal Applications
Applications that reason with multiple modalities like text, images, documents, and even audio processing a scanned form, generating a description for an image, or matching up a specification to support conversations.
7. LLM-powered Business Applications
Full-fledged business applications with a large language model as their core, custom solutions for internal use or customers, redesigned from the ground up using capabilities of GenAI.
8. Custom Prompt & Model Workflows
Engineered, tested, and controlled prompt chains and model pipelines, built to perform reliably in production, rather than work only once during a demo.
Core Capabilities
Content Creation
Brand-aligned content drafts for marketing, product, and internal use created in minutes, not days
Summarization
Long-form text and communications distilled down to the key elements relevant to decision-making
Intelligent Search
Find the answers by meaning and intent, not through matching exact keywords
Conversational AI
Seamless chat and voice interaction that doesn’t lose its memory between questions
Recommendations
Recommendations based on reality and user behavior, not guesswork and generalizations
Multimodal AI
A single interaction to comprehend text, images, and documents all at once
LLM Application Development
Complete applications and internal tools developed around the core language model
Prompt & Model Workflows
Robust AI behaviour through consistent, tested, repeatable prompt workflows
How We Decide What to Build
Just because it includes “AI” does not mean that every idea is worth implementing. Before implementation of each GenAI idea begins, the idea undergoes the exact same filter process, one that most vendors ignore.
This filter shields you from two potential consequences: AI capabilities that are impressive during a demo but do not provide any value, and problems that could have been solved easily but have been unnecessarily complicated with an LLM. Each GenAI product we deliver at JBAS has passed this test.
How We Decide What to Build — Every GenAI idea is filtered before it reaches development
Technologies We Build With
Foundation Models
GPT, Claude, Gemini, and open-source models (Llama, Mistral) depending on the use case, budget, and sensitivity of data
Multimodal Models
Image-language models for understanding images and documents
Backend & APIs
Python (Fast API), Node.js, REST/GraphQL for industrial-grade implementation
Evaluation & Testing
Prompt versioning, output evaluation, and regression testing before deployment
Deployment
Web, mobile, WhatsApp, Slack, Teams, or integration right into your application infrastructure
Cloud & Security
AWS, Azure, or GCP, plus encryption, access controls, and on-premises option for sensitive data
Industries We Develop for
IT & SaaS
Documentation generation for products, release note summary, AI search inside apps
BFSI
Report summary, statements summary, drafting of compliant content
Retail & E-commerce
Product description, personalization of recommendations, visual search
Healthcare & Life Sciences
Clinical note summary, FAQ generation for patients
Media & Marketing
Large-scale content drafting, draft copies for marketing campaigns, summary of transcripts
Manufacturing & Logistics
Technical document summarization, multimodal reporting on inspection results
Professional Services
Drafting of proposals and reports, case file summary, research support.
Frequently Asked Questions
Ready to implement generative ai solutions?
Tell us a bit about what you need — our engineering team will get back to you to scope the project and next steps.