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NASBIX TECHNOLOGIES

AI that ships to production—not slide decks

LLM applications, RAG, agents, and intelligent automation grounded in your data—with evals, guardrails, cost controls, and security reviews built into every sprint from Karachi.

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RAG & enterprise data Agents & copilots Evals & guardrails Named solution architects
AI service

From pilot hype to measurable outcomes

Most AI stalls after a demo: wrong data boundaries, no evaluation harness, runaway token costs, or compliance teams that cannot sign off. NASBIX builds AI features inside your product and ops workflows—use-case first, with architecture your engineering team can own after handover.

We deliver from Karachi for fintech, healthcare, ecommerce, logistics, and SaaS teams that need copilots, document intelligence, support automation, and decision assist—not generic chatbots pasted onto a homepage. Named architects pair with your domain experts so prompts, retrieval, and human-in-the-loop review match how work actually happens.

  • Use-case discovery tied to KPIs—time saved, conversion, deflection, risk reduction
  • RAG and tool-using agents on your APIs, docs, and warehouses—not public web guesswork
  • PII handling, access control, audit logs, and secure SDLC aligned with your policy
  • Observability for quality, latency, cost, and drift after go-live
Machine learning → AI SEO →
Artificial Intelligence development by NASBIX TECHNOLOGIES
RAG · Agents · Guardrails
Who we help

Built for regulated and revenue-critical products

Greenfield AI features, copilot rollouts, and hardening pilots that never left staging.

Product & SaaS teams

In-app assistants, onboarding copilots, and smart search that increase activation and retention.

Operations & support

Ticket triage, knowledge retrieval, and workflow automation with human review where it matters.

Document-heavy domains

Extraction, classification, and Q&A on contracts, claims, invoices, and clinical or financial records.

What you get

AI capabilities that matter

End-to-end delivery—not a model API key and a hope.

Strategy & use cases

Prioritized backlog, success metrics, and build-vs-buy guidance for LLMs and classical ML together.

RAG & knowledge

Chunking, embeddings, retrieval tuning, and citation UX on Confluence, SharePoint, tickets, and warehouses.

Agents & automation

Tool-calling workflows, approvals, and integrations with CRM, ERP, and internal APIs—bounded and testable.

Generative UX

Copilots, drafting, summarization, and multimodal flows embedded in web and mobile products.

Evals & safety

Golden sets, red-team scenarios, PII filters, policy prompts, and human review queues.

LLMOps & cost

Routing, caching, fallbacks, monitoring, and finops so production usage stays predictable.

Trust by design

Enterprise AI needs boundaries—not blind trust

We design for least privilege, data residency, and auditability so legal, security, and compliance can approve real rollouts—not block them after the pilot.

  • Data classification, retention, and opt-out paths for sensitive corpora
  • AuthZ on retrieval sources and tools—agents inherit user permissions
  • Secrets, key rotation, and no training on your data without explicit agreement
  • Logging, tracing, and feedback loops for incident response and tuning
  • Model/vendor selection with latency, cost, and jurisdiction constraints
  • Secure SDLC reviews on prompts, plugins, and third-party connectors
Secure SDLC → Fintech industry →
Enterprise AI security and governance practices
Governance · Data · Production ops
How we deliver

From discovery to governed production

Thin vertical slices with evals in CI—so each demo is a step toward sign-off, not a one-off hackathon.

  1. 01 · DiscoverWorkflows, data sources, compliance constraints, KPIs, and integration surface.
  2. 02 · PrototypeRetrieval/agent architecture, eval harness, and UX for trust (citations, edits, escalation).
  3. 03 · BuildProduction APIs, auth, monitoring, cost controls, and pilot with real users.
  4. 04 · ScaleRollout playbook, training, drift monitoring, and optional managed AI pod.
Engagement models

Buy the way you ship AI

AI discovery sprint

Two–three week use-case workshop, data readiness review, and prioritized roadmap with ROI framing.

Copilot MVP

Fixed-scope RAG or agent feature with evals, guardrails, and one primary system integration.

Product AI squad

Embedded team shipping multiple AI surfaces across web, mobile, and back-office tools.

AI hardening & ops

Upgrade pilots to production—cost, safety, monitoring, and compliance gaps closed.

Explore more

Related data & AI paths

Classical ML, data platforms, and innovation programs that pair with LLM work.

Machine learning Big data AI SEO Innovation hub

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