Generative AI & RAG
Build assistants that work with approved company knowledge using retrieval pipelines, embeddings, vector search, source-aware responses and controlled access.
Techniskera Service
AI, GenAI & Automation
Practical AI systems that improve support, sales, operations, knowledge access, content workflows and decision making.
Capabilities
What we can build for you
A flexible capability set that can be scoped for a single requirement or combined into a larger technology initiative.
✓ AI Agents & AssistantsPlanned around your users, workflow, technical environment and business priorities.
✓ RAG Knowledge SystemsPlanned around your users, workflow, technical environment and business priorities.
✓ Document IntelligencePlanned around your users, workflow, technical environment and business priorities.
✓ LLM IntegrationsPlanned around your users, workflow, technical environment and business priorities.
✓ Workflow AutomationPlanned around your users, workflow, technical environment and business priorities.
✓ Chatbots & CopilotsPlanned around your users, workflow, technical environment and business priorities.
✓ AI SearchPlanned around your users, workflow, technical environment and business priorities.
✓ Business Process AutomationPlanned around your users, workflow, technical environment and business priorities.
Where It Fits
Practical capability for real operating needs.
We apply AI and machine learning where they can remove friction, improve decisions or make knowledge easier to use. The work can range from a focused automation to a production AI product with retrieval, model evaluation, monitoring and human review.
- Generative AI assistants and copilots
- RAG systems grounded in approved business knowledge
- Document extraction, classification and summarization
- Predictive models for demand, risk, churn or prioritization
- Natural language processing and intelligent search
- Computer vision workflows where image understanding is useful
- AI-enabled customer support and sales workflows
- Machine-learning APIs embedded inside existing products
Engineering Priorities
Built for production, not a demo.
Data readiness and use-case validationIncluded in planning and delivery where relevant to the engagement.
Prompt, retrieval and model evaluationIncluded in planning and delivery where relevant to the engagement.
Vector search and knowledge indexingIncluded in planning and delivery where relevant to the engagement.
Guardrails, permissions and human-in-the-loop reviewIncluded in planning and delivery where relevant to the engagement.
Model/API cost and latency optimizationIncluded in planning and delivery where relevant to the engagement.
MLOps, monitoring and continuous improvementIncluded in planning and delivery where relevant to the engagement.
AI & Machine Learning
From experiments to production-ready intelligence.
AI value comes from the complete system around the model: useful data, retrieval, evaluation, permissions, user experience, monitoring and a workflow people can trust.
Predictive Machine Learning
Use historical business data for forecasting, scoring, classification, recommendations and prioritization with measurable validation instead of guesswork.
AI Automation
Connect AI to CRM, support, documents, email, APIs and internal workflows so outputs can trigger useful actions while retaining human approval where needed.
MLOps & AI Operations
Plan model versioning, evaluation, monitoring, latency, cost, privacy and production support so AI systems remain dependable after the initial launch.
Business Value
Designed to solve a problem, not simply deliver a feature.
We define the expected outcome before implementation: better customer experience, faster operations, improved reliability, reduced manual work, stronger visibility, easier reporting or a scalable foundation for growth.
Technical choices are then made around maintainability, security, performance, integration requirements and the capability of the team that will operate the solution after launch.
Clear ScopePriorities, assumptions, dependencies and success criteria are made explicit.
Quality EngineeringResponsive UX, testing, performance, security and clean implementation practices.
Integration ReadyAPIs and data flows are considered as part of the system, not as an afterthought.
Long-term SupportWe can continue with maintenance, optimization and new feature delivery.
Delivery Model
From requirement to production
A straightforward process with visible milestones and room for iterative feedback.
01
Assess
Understand requirements, users, current systems and the desired business outcome.
02
Architect
Define solution design, technology choices, integrations, risks and milestones.
03
Deliver
Design, develop, test and review the solution in planned iterations.
04
Launch & Improve
Deploy, monitor, support and evolve the solution based on real use.
Start a Project
Tell us what you want to build.
Share your requirement for ai, genai & automation. We will receive the enquiry at contact@techniskera.com.
WhatsApp