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Assistora

AI & Intelligent Automation

Build Intelligence Into Your Business.

From retrieval-augmented assistants and AI agents to predictive models and computer vision, we design, build and operate AI systems that are grounded in your data, evaluated rigorously and safe to run in production.
Discuss AI SolutionsExplore capabilities
  • Generative AI & RAG
  • AI agents
  • Machine learning
  • MLOps & evaluation

Overview

Artificial Intelligence at Assistora

Modern AI makes it possible to automate knowledge work, personalise experiences and extract insight from unstructured data at a scale that was impractical only a few years ago. The difficult part is not the demo — it is reliability, data security, evaluation, cost control and integration with the systems your people already use.

Assistora approaches AI as an engineering discipline. We start with a clearly defined use case and success measure, choose the simplest approach that meets it, and build the evaluation, guardrails and observability needed to run it with confidence.

Business challenges

The problems we help you solve.

  1. 01

    Pilots that never reach production

    Promising prototypes stall because of accuracy, security or integration concerns.

  2. 02

    Unreliable answers

    Language models without grounding produce confident but incorrect output.

  3. 03

    Data privacy concerns

    Sensitive data must be protected when it flows through AI services.

  4. 04

    Unclear return on investment

    Without defined metrics it is hard to know whether an AI feature is creating value.

Capabilities

What we deliver.

End-to-end artificial intelligence expertise, from strategy through implementation and ongoing operation.

  • Generative AI

    Content generation, summarisation and extraction features built on leading foundation models with structured outputs and guardrails.

  • Enterprise AI Assistants

    Secure internal assistants that answer questions from your documents and systems with citations and access control.

  • AI Agents & Automation

    Tool-using agents that complete multi-step workflows with human approval points, audit trails and clear failure handling.

  • Retrieval-Augmented Generation

    Ingestion, chunking, embeddings, hybrid search and re-ranking pipelines that ground responses in trusted sources.

  • LLM Integration

    Integrating language models into existing products and APIs with caching, fallbacks, cost controls and observability.

  • Voice AI

    Speech-to-text, text-to-speech and conversational voice experiences for support, intake and accessibility.

  • Chatbots

    Customer-facing conversational experiences with escalation to human agents and consistent brand voice.

  • Machine Learning Solutions

    Classification, forecasting, recommendation and anomaly detection models trained and validated on your data.

  • Computer Vision

    Image and video understanding for inspection, document processing and visual search.

  • Natural Language Processing

    Entity extraction, classification, sentiment and document understanding pipelines.

  • Predictive Analytics

    Forecasts and risk scores delivered into the dashboards and workflows where decisions are made.

  • MLOps

    Versioned data and models, automated training and evaluation, deployment pipelines and drift monitoring.

Platforms & technologies

The stack we work with.

Technology choices are always driven by your context. Listing a technology does not imply a vendor partnership.

Models & platforms

  • OpenAI API
  • Anthropic Claude
  • Google Gemini
  • Azure OpenAI
  • Amazon Bedrock
  • Vertex AI
  • Open-weight models

Frameworks

  • LangChain
  • LlamaIndex
  • PyTorch
  • TensorFlow
  • scikit-learn
  • Hugging Face

Retrieval & data

  • pgvector
  • Pinecone
  • Weaviate
  • Elasticsearch
  • BigQuery

Operations

  • MLflow
  • Weights & Biases
  • Kubeflow
  • OpenTelemetry

Typical solutions

Where clients usually start.

  • 01

    Knowledge assistant

    A secure assistant that answers policy, product or engineering questions from internal documentation with source citations.

  • 02

    Document intelligence

    Automated extraction and validation of data from invoices, contracts or forms into downstream systems.

  • 03

    Support automation

    AI-assisted triage, suggested replies and self-service resolution for customer support teams.

  • 04

    Demand forecasting

    Machine learning forecasts that feed inventory, staffing or capacity planning.

Delivery process

How we deliver.

A clear, iterative path from discovery to measurable results.
  1. 01

    Discover

    Workshops and technical discovery to understand goals, constraints, current systems and success measures.

  2. 02

    Define success

    Agree the use case, users, risks and measurable evaluation criteria before any model is chosen.

  3. 03

    Prototype & evaluate

    Build a focused prototype and test it against a representative evaluation set.

  4. 04

    Engineer for production

    Add security, access control, guardrails, monitoring and cost controls; integrate with your systems.

  5. 05

    Operate & improve

    Track quality and usage in production, collect feedback and continuously improve.

Business benefits

What it means for your business.

  • Productivity

    Automate repetitive knowledge work so teams focus on judgement and relationships.

  • Better decisions

    Predictions and insights delivered where decisions are actually made.

  • Trustworthy output

    Grounding, evaluation and guardrails make AI behaviour measurable.

  • Responsible adoption

    Privacy, security and human oversight designed in from the start.

Relevant industries

Applied across sectors.

FAQs

AI questions, answered.

We design solutions using enterprise API terms or private deployments that do not use your data for model training, and we document data flows so your security team can review them.

We ground responses in retrieved sources, constrain outputs, cite evidence, and measure accuracy against evaluation sets. Where stakes are high, we add human review steps.

Often not at first. Retrieval, prompt design and structured outputs solve most problems more cheaply. We recommend fine-tuning when evaluation shows a clear benefit.

A focused proof of value can typically be built and evaluated in a few weeks, depending on data access and scope. Production rollout follows once success criteria are met.

Related services

Often delivered together.

AI & Data

Data Engineering

Reliable pipelines, modern warehouses and real-time streaming that turn raw data into trusted decisions.

  • BigQuery
  • Snowflake
  • Amazon Redshift

Software Engineering

Custom Software Engineering

Custom applications, microservices and integrations engineered around how your business actually works.

  • TypeScript
  • Python
  • Go

Cloud & Infrastructure

Cloud Computing

Design, migrate and operate secure, cost-efficient cloud environments across AWS, Google Cloud and Microsoft Azure.

  • AWS
  • Google Cloud
  • Microsoft Azure

Ready to talk AI?

Share your goals and constraints. An Assistora engineer will respond with practical next steps.

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