Services · LLM & Generative AI

LLM & Generative AI

DIGIT Pakistan designs, builds and deploys production-grade LLM systems — RAG pipelines, domain-tuned chatbots, autonomous agents and AI workflows that plug into your existing products and scale reliably.

What We Build

LLM Capabilities

Production AI — not proofs of concept.

Retrieval-Augmented Generation (RAG)

We connect LLMs to your private data — documents, FAQs, knowledge bases and APIs — so answers are grounded, verifiable and up-to-date instead of hallucinated.

PineconeWeaviatepgvectorLlamaIndex

Intelligent Chatbots & Assistants

Conversational AI for support, onboarding or internal enablement. Tuned tone-of-voice, guardrails and escalation logic that feels on-brand and safe.

GPT-4oClaudeStreamingMemory

Autonomous & Multi-step Agents

Task-focused agents that read, write and act across your tools — CRMs, ticketing, internal APIs — to automate repetitive workflows under human supervision.

LangChainTool UseFunction CallingMCP

Model Evaluation & Safety

Evaluation harnesses, red-teaming, prompt hardening and fallbacks so your AI features behave reliably in real-world use, not just in demos.

EvalsRed TeamGuardrailsMonitoring
Our AI Stack

Built With Best-in-Class AI Tools

We combine hosted models with open-source tooling based on your data sensitivity, latency and cost requirements.

Foundation Models

GPT-4o · Claude · Gemini · Llama · Mistral

RAG & Orchestration

LangChain · LlamaIndex · Custom pipelines · Observability

Vector Stores

Pinecone · Weaviate · pgvector · Qdrant · ChromaDB

Backend & Infra

Python · FastAPI · Node.js · AWS · Docker · Queues

LLM FAQ

Common Questions

DIGIT designs and ships retrieval-augmented chatbots, internal knowledge assistants, AI copilots for SaaS products, document automation workflows and task-specific agents — mainly for B2B, SaaS and public-sector use cases.

Let's build AI that works

Whether you need a RAG chatbot, an internal knowledge assistant, or a full multi-agent system — tell us the problem and we'll propose the solution.