AI & Automation · LLM applications
We add LLM capabilities to existing web apps and internal tools: assistants, summarisation, search and Q&A over company documents using retrieval-augmented generation (RAG), and content generation. We build on OpenAI, Azure OpenAI or AWS Bedrock, with guardrails, evaluation and cost control from the start.
What we build
Typical pieces of work in this area. Most engagements combine several of them.
Ask questions across policies, manuals, contracts and wikis, with citations to the source passage so people can check every answer.
A context-aware helper inside your web app or portal that explains data, drafts responses and guides users through tasks.
Consistent summaries of long tickets, call notes, reports or email threads that your team can skim in seconds.
Drafts of product descriptions, proposals or replies generated from your data and style guide, always checked by a person before they go out.
Turn unstructured emails and documents into validated fields your systems can store, with confidence checks and fallbacks.
Search that understands meaning, using embeddings in PostgreSQL with pgvector or Azure AI Search, alongside your existing keyword search.
Prompt-injection defences, output validation, test sets built from real examples and dashboards for quality, latency and cost.
How we work
Week 1
Agree the task, the users, the source content and what a good answer looks like.
Weeks 1–3
A working slice on your real content, so stakeholders can try it within weeks.
Gate
Score answers against a test set, probe failure cases and compare models on quality and cost.
Build
Wire into your app with the same sign-in and permissions, add guardrails, logging and limits.
Ongoing
Track quality, feedback and spend in production, and refine content and prompts over time.
Proven, well-supported tools, chosen for your context rather than for novelty.
Outcomes depend on your starting point; we agree success measures with you up front.
Typical use cases
Staff ask questions in plain language and get answers with links to the exact clause in the handbook.
Customers get answers from your documentation and their own account data before raising a ticket.
Sales teams generate a first draft from CRM data and approved templates, then edit and send.
Support agents see a short summary and suggested next step at the top of every long ticket.
Representative projects
A mid-size engineering consultancy
A permission-aware assistant that answers staff questions from procedures, project archives and templates, citing the source document every time.
A multi-site wholesale distributor
Supplier invoices read with AI Builder, matched to purchase orders and created as draft purchase invoices in Business Central for an accountant to approve.
Representative engagements. Client names and some details are withheld or illustrative.
FAQ
Can’t find what you’re looking for? Ask us directly. We’re happy to talk it through.
Keep exploring
Support and helpdesk assistants, and tool-using agents that act in your systems with human approval.
Pipelines, warehouses and lakehouses, Power BI and Microsoft Fabric dashboards, and predictive analytics.
Fast, accessible web apps and APIs built with React, Next.js, Node.js and TypeScript, engineered to scale with your product.
Client portals, workflow automation and knowledge tools for firms that sell expertise.
Start a conversation
Tell us what you’d like it to do and where the information lives. We’ll help you judge feasibility before you spend on a build.
Prefer email? contact@blackpantherdigital.net
Product and company names mentioned on this page are trademarks of their respective owners. Black Panther Digital Solutions is an independent company and is not affiliated with, partnered with or endorsed by OpenAI, Microsoft, Amazon, Anthropic or any other AI vendor.