Artificial Intelligence & Generative AI
Intelligence, engineered for production.
We turn AI ambition into dependable systems: assistants grounded in your knowledge, agents that finish real work and models you can measure, audit and trust.
01 Overview
An impressive AI demo takes an afternoon; AI that holds up under real users, real data and real audits takes engineering. That is the gap TEQHAND closes — with systems grounded in your knowledge, governed by design and measured against business outcomes.
We build retrieval-augmented assistants, autonomous agents, document intelligence and predictive models, and the evaluation, security and MLOps foundations that keep them trustworthy at scale.
02 Business challenges
AI & Generative AI challenges we solve.
Stuck in pilots
Promising prototypes never reach production or real users.
Hallucination risk
Ungrounded answers erode trust and create compliance exposure.
Data readiness
Knowledge is scattered across documents, tickets and systems.
Unclear ROI
Without evaluation and telemetry, value is hard to prove.
03 Our solutions
How we deliver AI & Generative AI.
- 01
AI strategy & use-case portfolio
Prioritized opportunities scored by value, feasibility and risk.
- 02
RAG & enterprise knowledge
Grounded assistants with citations, permissions and evaluation.
- 03
AI agents & automation
Tool-using agents that complete multi-step work with human oversight.
- 04
ML & MLOps
Forecasting, classification and personalization with production pipelines.
04 Key capabilities
AI & Generative AI capabilities.
- Generative AI applications
- Retrieval-Augmented Generation
- AI agents & orchestration
- Chatbots & virtual assistants
- Intelligent document processing
- Predictive analytics
- LLM evaluation & guardrails
- MLOps & model monitoring
05 Technology stack
Our AI & Generative AI toolkit.
Models
- Claude
- GPT
- Gemini
- Llama
- Mistral
Frameworks
- LangGraph
- LlamaIndex
- PyTorch
- scikit-learn
Data & Ops
- pgvector
- Pinecone
- MLflow
- Databricks
06 Benefits
- Faster knowledge retrieval Employees find grounded answers in seconds.
- 60%
- Less manual processing Documents and workflows automated end-to-end.
- 40%
- Pilot to production With evaluation and guardrails from day one.
- 8–12 wks
Indicative outcomes based on typical engagements; actual results vary by context.
07 Delivery method
Our AI & Generative AI delivery method.
- 01
Frame the use case
Business owners, data owners and engineers agree on the task to improve and how success will be scored.
- 02
Build the evaluation set
Real examples and expert answers become the benchmark for every prompt, model and retrieval change.
- 03
Prototype on real data
A working slice runs on your own documents and systems within weeks — not a demo on sample data.
- 04
Harden for production
Guardrails, access controls, monitoring and human-review paths are added before anyone depends on it.
- 05
Measure and expand
Usage, accuracy and cost telemetry guide the next use cases and the shared platform beneath them.
08 Use cases
AI & Generative AI in action.
Support copilot
Agents draft accurate, cited answers from your knowledge base.
Claims intake automation
Extract, validate and route documents with human-in-the-loop review.
Clinical documentation
Summaries and coding suggestions that reduce administrative load.
Related services
Ready to explore AI & Generative AI?
Bring one process or question you’d like AI to handle. We’ll tell you honestly whether it’s ready for production — and what it would take.