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AIAn Alian Software company
AI & Machine Learning

AI & Machine Learning

Intelligent solutions that learn and adapt.

From predictive analytics to AI agents, we build production-grade AI systems that deliver measurable business impact — not just buzzwords.

Why leading companies choose us

What you get that a generic ai & machine learning vendor does not.

Production, not notebooks

A model that only runs on a data scientist's laptop has not shipped. We build the whole path.

Evaluation before deployment

A golden dataset and a scoring harness exist before anything reaches a user.

Honest about feasibility

Some problems do not have enough signal in the data. We would rather say so in week two.

Cost modelled up front

Inference cost per prediction is a design constraint, not something discovered on the first invoice.

Humans where it matters

Irreversible actions get a human gate regardless of how confident the model reports itself to be.

Monitored after launch

Drift detection and scheduled re-evaluation, because quality decays quietly otherwise.

How we build

AI & Machine Learning built on foundations that hold

The data floor first

Most projects fail on data access and labelling, not modelling. We deal with that before touching a model.

Baselines before complexity

A simple model and a rules baseline first, so we can prove the sophisticated version earns its cost.

Evaluation as a permanent system

Suites that keep running weekly, growing from real production failures rather than launch-day cases.

Explainability where required

In regulated settings every prediction carries the inputs and the reasoning behind it.

What you get

  • AI agents & automation — custom outcome-targeted agents that watch, decide, and act, with humans in the loop where it matters
  • Custom AI apps & chatbots — RAG-powered knowledge bots with hybrid search, reranking, and cited answers
  • Predictive analytics & ML models for churn prediction, demand forecasting, anomaly detection, and quality scoring
  • Computer vision — image classification, object detection, OCR, and document understanding pipelines
  • Generative AI & content pipelines, plus AI strategy, governance, and team training workshops

Custom ai & machine learning for you

The capability most clients come to us for, and the work that surrounds it.

Our flagship capability

Machine learning development services

Predictive models that reach production and stay there — demand forecasting, anomaly detection, computer vision and scoring, with the data pipeline, evaluation harness and monitoring that keep them honest.

Key features

  • Predictive and forecasting models
  • Computer vision and defect detection
  • Anomaly and fraud scoring
  • Evaluation harness and drift monitoring
  • Explainable outputs where regulation requires

01

Computer vision

Defect detection, quality inspection and document understanding, with confidence thresholds and human escalation.

02

Predictive analytics

Forecasting demand, churn and failure, delivered as a usable range rather than false precision.

03

Data engineering

The pipelines, feature stores and warehousing that any model depends on to work at all.

04

Model operations

Deployment, versioning, monitoring and scheduled retraining once the model is live.

How we work

Every stage, and what it produces

The same nine stages on every engagement. What changes is what each one has to answer for ai & machine learning.

  1. Business evaluation

    01

    The decision this is meant to improve, and what a better decision is worth in money.

  2. Information gathering

    02

    A hard look at the data: what exists, who owns it, how clean it is, how far back it goes.

  3. Consultation

    03

    A feasibility session where we say plainly whether the signal is there.

  4. Designing the UI

    04

    Interfaces designed so a prediction is actionable rather than just displayed.

  5. User experience

    05

    The human workflow around the model, including what happens when it is wrong.

  6. Tech inspection

    06

    An audit of your existing data platform before we propose adding to it.

  7. Development

    07

    A baseline first, then complexity only where it measurably beats the baseline.

  8. QA and testing

    08

    Evaluation against a held-out set, plus adversarial cases and cost-per-prediction checks.

  9. Support and care

    09

    Monitoring, retraining schedule, and a named owner for the evaluation suite.

Everything we hand over at the end is listed on the handoff page.

When this is the right fit

Straight answers on where this service earns its cost — and where it does not.

  • Production-Grade Models — Battle-tested ML models with monitoring, drift detection, and automated retraining — not just notebooks.
  • Responsible AI — Built-in bias detection, explainability, and governance aligned with NIST AI RMF and EU AI Act compliance.
  • Full-Stack AI Engineering — From data pipeline to model serving to frontend — we build the entire stack, not just the model.
  • Multi-Model Architecture — Orchestrate Claude, OpenAI, open-source models, and custom fine-tunes — pick the right model for each task.
  • Measurable ROI — Every project starts with a business outcome metric. We measure what matters, not just model accuracy.
  • Rapid Prototyping — Working proof-of-concept in 2-3 weeks. Validate ideas fast before committing to full production builds.
  • Human-in-the-Loop — Smart escalation logic and confidence thresholds ensure humans stay in control where it matters.
  • Observability Built In — Full telemetry — logged decisions, cost tracking, latency monitoring, and eval suites from day one.

Track record

15+
Years shipping software
Alian Software since 2010
84%
Retainer renewal rate
Clients who extend past the first term
4–8
Weeks to first production ship
Typical fixed-fee sprint
See the evidence

Sample builds

Shapes of work we ship most often in this pillar.

Intelligent document processing

Extract, classify, and route information from invoices, contracts, and forms — reducing manual data entry by 85% with human review for edge cases.

Product recommendation engine

Collaborative filtering + content-based hybrid model serving personalized recommendations — 23% increase in average order value.

Predictive demand forecasting

Time-series ML model trained on sales history, seasonality, and external signals — reducing overstock by 30% and stockouts by 45%.

Tech we reach for

Chosen per project. We will tell you when the boring option is the right one.

  • Python / PyTorch / scikit-learn
  • Anthropic Claude / OpenAI
  • LangChain / LangGraph
  • Hugging Face
  • pgvector / Pinecone
  • MLflow / Weights & Biases
  • AWS SageMaker / Modal

Client reviews

What our clients are saying

Reviews from clients we have delivered for.

  • It is always a challenge to work with outsourced resources, and even so, Alian exceeded my expectations.
    Avi Landy
  • Alian Software development work is excellent, our clients are happy, and we continue to lean on them more as they get more integrated with our company.
    Scott Lawrence
  • They are incredibly helpful and adaptable, and always create something that leaves our clients satisfied.
    Meghan Kennedy
  • They were extremely patient with adjustments and changes on our side.
    Brad Davies
  • I don't even know if I'd be where I am today without them because they really brought my vision to life.
    Shreen Ghaleb

Got questions? We have answers.

  • It depends on the problem. For LLM-powered features (summarization, extraction, Q&A), you can start with zero training data. For custom ML models, we need enough labeled examples — usually hundreds, not millions. We'll tell you honestly if your data is ready.

No obligation, no deck

Talk to a human about this

Tell us the problem. If ai & machine learning is not the right answer, we will say so and point you at what is.

24h

Typical reply time on weekdays