[ 01 / Services — AI Development ]

    AI THAT
    ships.

    Generative AI, autonomous agents and ML systems engineered for accuracy, latency and ROI — by senior data scientists and AI engineers.

    GenAI · LLMsAgents · RAGVision · NLPMLOps
    0+

    AI sprints shipped

    0+

    Industries served

    <0wk

    Avg. PoC turnaround

    0%

    Client retention

    [ Why Seraphic ]

    WHY
    Seraphic for AI.

    We pair deep data science craft with serious product engineering. Our teams build robust LLM and ML systems engineered for accuracy, scale and a measurable business outcome — not lab demos. We own the path from problem framing to MLOps so AI quietly compounds value across your operation.

    • Senior LLM and ML engineers, not generalists handed a prompt
    • Eval-driven development with reproducible benchmarks
    • Private VPC, BYOK and SOC2-aligned engineering practices
    • Strategy, fine-tuning, deployment and MLOps under one roof
    • Cloud-native — AWS SageMaker, Vertex AI, Azure ML

    [ Solutions ]

    AI solutions across your business ecosystem.

    Think beyond isolated algorithms. We build AI that integrates with your data, product and team — designed for operational impact from day one.

    Predictive Analytics & Forecasting

    Anticipate demand, churn and operational needs to drive proactive decisions.

    Recommendation Engines

    Personalised product, content and pricing experiences powered by behavioural data.

    Generative AI Applications

    LLM copilots, chatbots and content systems with retrieval, memory and tool use.

    Intelligent Automation (RPA + NLP/CV)

    Bots that understand text, parse documents and act across systems.

    Computer Vision Pipelines

    OCR, defect detection, skin analysis, video analytics — edge or cloud.

    Cloud-Native MLOps

    Scalable training, serving, monitoring and governance on AWS, GCP or Azure.

    [ 01 — Capabilities ]

    WHAT WE
    deliver.

    01

    Generative AI products

    Multimodal LLM apps with retrieval, memory and tools — fine-tuned to your domain.

    02

    Autonomous AI agents

    Agents that reason, browse, call APIs and ship work — for sales, support, research.

    03

    RAG & vector search

    Hybrid retrieval with reranking, citations and grounding — tuned for accuracy and cost.

    04

    Computer vision

    OCR, document AI, defect detection, skin/health analysis. Edge or cloud, mobile-ready.

    05

    Conversational AI

    Voice agents, chatbots and copilots wired into your CRM, ERP or product surface.

    06

    MLOps & evaluation

    Eval harnesses, observability, drift monitoring, prompt versioning and CI/CD.

    [ Our approach ]

    METHOD over magic.

    01

    Data-Centric Strategy & Preparation

    Great AI starts with great data. We deeply understand your problem, identify the right data sources, and execute rigorous cleansing, transformation and feature engineering for the highest quality input.

    • Clear problem definition and KPI alignment
    • Data discovery, collection and validation
    • Advanced cleansing & transformation
    • Strategic feature engineering
    02

    Rigorous Model Development & Validation

    We select the right algorithms — classification, regression, deep learning or LLMs — train with best practices, run hyperparameter sweeps, and validate against precision, recall, F1 and AUC.

    • Diverse ML & deep learning architectures
    • Cross-validation and ablation studies
    • Hyperparameter optimisation
    • Comparative model benchmarks
    03

    Scalable Deployment & MLOps

    An AI model only creates value when deployed reliably. We ship to API, mobile or edge, set up drift monitoring and implement MLOps pipelines for automated retraining and lifecycle management.

    • Cloud or on-prem deployment
    • Performance & drift monitoring
    • Automated retraining pipelines
    • Production-grade scalability
    04

    Continuous Improvement & Ethical AI

    AI is not a one-time project. We monitor, A/B test, retrain and ensure adherence to responsible AI principles — fairness, transparency and accountability across the lifecycle.

    • Continuous evaluation & retraining
    • Bias and fairness audits
    • Explainability & governance
    • Roadmap aligned with AI research

    [ End-to-end ]

    COMPREHENSIVE
    services.

    From discovery to deployment and beyond — a single team across strategy, design, engineering and operations.

    01

    AI Strategy & Consulting

    02

    Custom ML Model Development

    03

    Generative AI & LLM Apps

    04

    NLP Solutions

    05

    Computer Vision Solutions

    06

    AI Agent & Chatbot Engineering

    07

    Predictive Analytics

    08

    MLOps & AI Platform

    [ Tech stack ]

    TOOLS WE
    trust.

    PythonTypeScriptRSQLGo

    [ Engagement ]

    HOW WE
    ship.

    01

    Discovery sprint

    1–2 weeks. Use-case scoring, data audit, feasibility model and a costed roadmap.

    02

    Prototype

    2–4 weeks. Working LLM/agent prototype against real data with a clear eval baseline.

    03

    Production build

    6–12 weeks. Hardened pipelines, security, infra, observability, integrations.

    04

    Iterate & scale

    Continuous evaluation, fine-tuning, cost optimisation and roadmap execution.

    [ Industries ]

    WHO WE
    serve.

    • Healthcare
    • Fintech
    • EdTech
    • E-commerce
    • SaaS
    • Media
    • Real estate
    • Logistics

    [ Engage with us ]

    FLEXIBLE
    models.

    Proof of Concept (PoC)

    2–4 weeks. De-risk a hypothesis with real data and an eval baseline.

    Pilot project

    6–10 weeks. Production-shaped MVP with one user cohort live.

    Full implementation

    3–6 months. End-to-end build, integrations and MLOps.

    Embedded AI squad

    Ongoing retainer. Embedded engineers, monthly roadmap reviews.

    [ FAQ ]

    GOOD
    questions.

    How much does an AI MVP cost?+

    Most production-ready AI MVPs land between $35k–$120k depending on data complexity, integrations and evaluation rigor.

    Do you fine-tune or use foundation models?+

    We start with foundation models + RAG and only fine-tune when evaluation data shows clear, measurable lift.

    How do you handle data privacy?+

    Private VPC deployments, BYOK, on-device inference where possible and SOC2-aligned engineering practices.

    Can you work with our existing engineering team?+

    Yes — we plug into your repo, sprints and reviews. Many engagements run as embedded squads.

    Which cloud do you support?+

    AWS, GCP and Azure. We use SageMaker, Vertex AI and Azure ML depending on your existing footprint.

    [ Now booking Q3 2026 ]

    LET'S BUILD
    YOUR AI advantage.

    One async intake, one 30-minute call, one tightly-scoped proposal. No procurement theatre.

    Let's make an impact together.
    sales@seraphic.io

    Copyright © 2026 Seraphic Infosolutions. All Rights Reserved.