ENGINEERING / APPLIED AI
Applied AI &
LLM Integration
Connect models to the work your system needs to do.
We integrate language models, knowledge sources and specialised AI services into working applications. From retrieval and structured outputs to APIs and background processes, BACore builds the software around the model.
FROM CONTEXT TO ACTION
01 / CONTEXT
Your data & knowledge
Documents · repositories · connected services
↓ retrieve relevant, permitted context
02 / MODEL
Generate a useful result
Structured data · a draft · a proposed action
↓ validate output and permissions
03 / APPLICATION
Move the workflow forward
Call an API · queue work · request human review
Reference integration pattern. The application controls execution, access and approval.
SYSTEMS IN PRACTICE / WAYFIX SUPPORT COPILOT
Turn scattered documentation into cited support guidance.
A completed RAG integration for WayFix’s contact-centre workflow.
THE USE CASE
Agents needed to find technical procedures across fragmented documentation while handling a live customer interaction.
WHAT WE IMPLEMENTED
Pinecone-based retrieval, Claude 3.5 Sonnet through Amazon Bedrock and cited answers inside WayFix’s proprietary CRM, integrated with Salesforce. Agents could approve suggested actions through WayFix’s API.
RESULTS
210 seconds → 12 seconds
Average documentation search time.
68% → 82%
First contact resolution: +14 percentage points.
Before-and-after results for the WayFix implementation.
SYSTEMS IN PRACTICE / AI VIDEO ORCHESTRATION
Turn a request into a video-production workflow.
A completed BACore project connecting AI generation, speech services and controlled software execution.
THE USE CASE
A person, an external application or an AI agent initiates a video request. Manual and AI-generated inputs become one production specification: script, mood, audio, actors, scenes and cameras.
WHAT WE IMPLEMENTED
Backend orchestration, AI and speech-service integrations, performance inputs, scene assembly and the rendering pipeline. Voice can come from supplied audio, the ElevenLabs API or local text-to-speech.
WHY THE INTEGRATION MATTERS
The production payload connects variable model output to explicit instructions for the software that assembles the finished video.
REQUEST
Form · API · agent
One entry workflow for people and integrations
↓
PRODUCTION DATA
Script · voice · scene specification
AI services contribute content and performance inputs
↓
EXECUTION
Assemble scenes & render
Software applies the production instructions
Simplified implemented workflow. Generated facial-reference footage is an intermediate input to the final 3D render.
WHAT WE INTEGRATE
Build around the task, the data and the action.
KNOWLEDGE
Retrieval & RAG
Connect a language model to selected source material. Design ingestion, retrieval, access filtering and source references around the questions the application needs to answer.
BUSINESS LOGIC
Structured outputs & tools
Turn generated content into validated records or proposed tool calls. Keep schemas, permissions and approval rules in the application before an external action runs.
SPECIALISED MODELS
Voice & multimodal workflows
Connect text, speech, images and model outputs to the same application workflow. Define what each stage consumes, produces and passes to the next service.
APPLICATION DELIVERY
APIs & background processing
Implement the connectors, queues, state transitions and review interfaces that make an AI capability usable within an existing product or a new system.
RAG IN ENGINEERING
Give the model relevant repository context.
Our engineering workflow implementation includes RAG over repository knowledge, alongside CodeRabbit and Graphite integration. Retrieval brings selected material into the task context.
For each integration, we define which sources may be retrieved, how they are updated and how output is checked. The evaluation covers retrieval quality as well as the model’s answer.
KNOWLEDGE
Repository material
Index the sources relevant to the task
↓ retrieve
TASK CONTEXT
Selected code & documentation
Provide the material needed for the current request
↓ generate & check
REVIEW
Output with supporting context
Evaluate usefulness and route changes through review
Conceptual RAG flow; source selection and review controls depend on the repository and task.
SYSTEMS IN PRACTICE / HOSTING SUITE
Connect execution to operational control.
The supporting backend engineering: instance lifecycle, service communication and visibility.
THE IMPLEMENTED USE CASE
Hosting Suite brings together an orchestrator, ServerLink, backend APIs and an operational dashboard. It manages server instances and connects their activity to application services.
Its RPC protocol over WebSockets and support for dedicated and on-premises environments demonstrate the integration and orchestration work behind a complete system.
SUPPORTING INFRASTRUCTURE
Orchestrate
Manage deployment and instance lifecycle.
Connect
Link server-side components with backend APIs.
Observe
Bring metrics, logs and management into the control interface.
This case demonstrates backend infrastructure and operational integration.
FROM INTEGRATION TO OPERATION
Define what a useful, acceptable result looks like.
We agree success criteria before building, then check the complete workflow against representative inputs and failure cases.
QUALITY
Evaluate the result
Check relevance, source support, schema validity and task completion. Keep representative examples to compare changes to models, prompts and retrieval.
CONTROL
Bound the action
Validate requests, restrict tool access and place approval where it is needed. Handle incomplete context and uncertain output explicitly.
OPERATIONS
Make failures visible
Track latency, usage and failed jobs. Design timeouts, retries and recovery around the effect each integration can have on the receiving system.
ARCHITECTURE + HANDS-ON IMPLEMENTATION
Where could AI move your workflow forward?
Bring a real task, example inputs and the system that needs the result. We can define the integration, evaluation criteria and implementation scope together.