HackSec Infotech

Service

AI & Machine Learning

LLM applications, computer vision and predictive models — evaluated, not just demoed.

The short version

AI & Machine Learning, the way we do it

The demo is the easy part. We build AI features that survive contact with real users: grounded in your data, measured against an evaluation set, guarded against prompt injection, and cheap enough per request to keep running.

  • Evaluation harness before production rollout
  • RAG grounded in your own knowledge base
  • Prompt-injection and data-leak hardening
  • Cost and latency budgets per request

Talk it through

Get a straight answer in 30 minutes

Bring the problem, not a spec. A senior engineer will tell you what we would do, roughly what it costs, and whether you even need us.

Book the call
  • NDA signed before scoping
  • Written proposal in 3 working days
  • No obligation, no sales pressure
−62%Manual review effort removed
94%Eval-set accuracy at handover
<900msp95 response latency

Figures are medians across comparable AI & Machine Learning engagements delivered since 2019.

What we deliver

AI & Machine Learning, end to end

LLM applications, computer vision and predictive models — evaluated, not just demoed.

LLM & agent applications

Assistants, copilots and workflow agents with retrieval, tool use, guardrails and human review paths.

Computer vision

Detection, OCR, quality inspection and video analytics deployed to cloud or edge devices.

Predictive analytics

Forecasting, churn, pricing and recommendation models wired into the systems that act on them.

Data & MLOps

Pipelines, feature stores, versioned training, drift monitoring and safe model rollout.

Technology

The AI & Machine Learning stack we trust

Chosen because it fits the problem and your team can maintain it — not because it trended last month.

  • Claude API
  • OpenAI
  • PyTorch
  • TensorFlow
  • LangChain
  • pgvector
  • Pinecone
  • Hugging Face
  • MLflow
  • Ray

How it runs

From first call to live in production

  1. Discover

    We interview your stakeholders and users, audit what exists, and write down the problem in one page everyone signs off on.

    • Stakeholder workshops
    • Technical audit
    • Success metrics defined
  2. Architect

    Solution architecture, threat model, delivery plan and a fixed-scope estimate — before anyone opens an editor.

    • System design
    • Threat modelling
    • Sprint roadmap
  3. Build

    Two-week sprints, demo every Friday, a staging URL from week one. You see progress continuously, not at the end.

    • Weekly demos
    • Code review gates
    • Preview environments
  4. Harden

    Automated tests, load testing and an internal penetration test on every build we ship. Security is a stage, not a hope.

    • QA automation
    • Pentest & fix
    • Performance budgets
  5. Launch

    Phased rollout, monitoring dashboards, runbooks and a documented handover to whoever operates it next.

    • Zero-downtime deploy
    • Observability live
    • Team handover
  6. Evolve

    Support SLAs, monthly reviews and a roadmap that responds to what real usage taught us after launch.

    • SLA-backed support
    • Usage analytics
    • Quarterly roadmap

Questions

AI & Machine Learning FAQs

AI & Machine Learning

Ready to talk about AI & Machine Learning?

Send a two-line brief. You will get a senior engineer on the call and a written proposal within three working days.

  • Free 30-minute discovery call
  • NDA signed before scoping
  • You own all code and accounts