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AISOFTAGENCY
AI that does real work inside your business.

AI & Automation

Production-grade AI assistants, RAG knowledge systems, agents and workflow automation that cut costs and create capacity.

At a glance

  • AI chatbots & assistants
  • RAG & document AI
  • AI agents
  • Workflow automation
Services
11
Technologies
9
Process steps
6
Overview

Why AI matters

AI creates value when it is embedded in real workflows — answering customers, reading documents, qualifying leads and connecting systems — not when it sits in a demo. We design and build AI solutions that are measured, safe and integrated with the tools you already use.

We are model-agnostic, working with OpenAI, Claude, Gemini and open-source models, and choose the right one for each task based on quality, latency, cost and data requirements. Every system ships with evaluations, guardrails, human hand-off and monitoring.

Challenges

Problems we solve

  • Teams buried in repetitive work

    Skilled people spend hours on triage, data entry and routine questions instead of high-value work.

  • Knowledge trapped in documents

    Answers exist in PDFs, wikis and inboxes, but finding them takes too long.

  • AI pilots that never ship

    Promising prototypes stall on accuracy, security or integration concerns.

What we offer

AI & Automation services

Benefits

What you gain

  • Hours back every week

    Automate high-volume, rules-heavy work end to end.

  • Instant, 24/7 responses

    Customers and employees get accurate answers in seconds.

  • Decisions from all your data

    AI that searches, summarises and reasons across your knowledge.

  • Enterprise-grade guardrails

    Evaluations, permissions, audit trails and human review built in.

Technology

Tools we trust

  • Node.js
  • OpenAI
  • PostgreSQL
  • Claude by Anthropic
  • Google Gemini
  • LangChain
  • Python
  • LlamaIndex
  • pgvector
Process

AI delivery process

A de-risked path from AI idea to a measured, production-grade system.

  1. 011 week

    Discovery

    We map the workflow, the decisions inside it and the business case, so AI is applied where it pays back.

    • Use-case map
    • ROI model
    • Success metrics
  2. 021–3 weeks

    Data

    We audit, clean and structure the knowledge, documents and system data the model will rely on — securely.

    • Data audit
    • Knowledge base
    • Access & privacy plan
  3. 032–3 weeks

    Prototype

    A working prototype on your real data within weeks, tested with the people who will actually use it.

    • Working prototype
    • Prompt & retrieval design
    • User feedback
  4. 042–6 weeks

    Integration

    We connect the AI to your CRM, help desk, ERP or internal tools with the guardrails production needs.

    • API integrations
    • Human hand-off flows
    • Guardrails
  5. 051–2 weeks

    Evaluation

    Automated evaluations and human review measure accuracy, safety, latency and cost before go-live.

    • Evaluation suite
    • Accuracy report
    • Cost projections
  6. 06Ongoing

    Production

    Launch with monitoring, analytics and continuous improvement as your data and needs evolve.

    • Monitoring
    • Usage analytics
    • Improvement roadmap
Client stories

What our clients say

  • “AISOFTAGENCY didn't sell us an AI demo — they redesigned our patient support workflow around it. Within three months the assistant was resolving most routine enquiries, and our team finally had time for the conversations that need a human.”

    Amira Haddad
    Amira HaddadChief Operating Officer, Lumora Health
    View project: An AI patient assistant that resolves 65% of enquiries
  • “Supplier paperwork used to consume entire days. Now documents are read, validated and posted to our ERP in minutes, with the tricky cases flagged for review. It simply works.”

    Kenji Watanabe
    Kenji WatanabeHead of Operations, Helixa Robotics
    View project: Document intelligence for supplier operations
FAQ

AI questions

Is our data safe when using AI models?

Yes. We use enterprise API agreements that exclude your data from model training, encrypt data in transit and at rest, apply role-based access and can deploy private or regional models when compliance requires it.

How do you make sure the AI gives accurate answers?

We ground responses in your approved knowledge with retrieval and citations, test against evaluation sets built from real questions, set confidence thresholds and route uncertain cases to people. Accuracy is monitored continuously after launch.

Which AI models do you work with?

We're model-agnostic. We regularly build with OpenAI, Claude and Gemini as well as open-source models, and select the best option per task based on quality, speed, cost and data requirements.

Let's build what's next

Have a project in mind?

Tell us where you want to go. We'll map the fastest route there — design, engineering, growth and AI included.