Applied AI · Enterprise IT Services

We build the intelligence layer for serious enterprises.

Grawity is an AI-first IT services studio. We design, train, and ship production-grade systems — retrieval, fine-tuned LLMs, agents, and guardrails — for organisations where the wrong answer is unacceptable.

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Industry domains
5
On-prem capable
Yes
Compliance-aware
By design
Engagement
Studio & retainer
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Retail· Finance· Manufacturing· Defence· Healthcare· Retail· Finance· Manufacturing· Defence· Healthcare·

Technologies we deploy in production

  • OpenAI
  • Anthropic
  • Llama
  • Mistral
  • Hugging Face
  • LangChain
  • vLLM
  • Pinecone
  • Postgres
  • Snowflake
  • Databricks
  • AWS · GCP · Azure

Our point of view

Most AI work today stops at the demo. Grawity exists for the harder half — turning a clever prototype into infrastructure your business can stake a quarter on. We treat models like components, evaluations like contracts, and guardrails like load-bearing walls.

  • Models Components, not magic

    Swappable, versioned, and owned like any other production dependency.

  • Evaluations Contracts, not vibes

    Golden sets, regression gates, and sign-off criteria before anything ships.

  • Guardrails Load-bearing walls

    Policy at input and output — structural, not bolted on after the fact.

  • Provenance Traceable by default

    Every generation cited, replayed, and defensible under audit.

Production-grade systems

RAG, fine-tuned LLMs, agents, and guardrails — built for environments where the wrong answer has real consequences.

Compliance by design

On-prem, VPC, and air-gapped deployments with provenance, audit trails, and model risk controls baked in from day one.

Senior team, fast delivery

Partner-led engagements with staff-level engineers. AI-native workflows that compress discovery-to-production without cutting corners.

Capabilities

A studio engineered for the hard parts of applied AI.

We work end-to-end across the AI stack — from data and retrieval to model training, agent orchestration, evaluation, and the boring-but-vital plumbing that keeps it running at 3am.

  1. 01MODELS

    LLM training & fine-tuning

    SFT, DPO, LoRA / QLoRA adapters, domain pre-training, and continual learning pipelines on Llama, Qwen, Mistral, and proprietary base models.

    • Curated & synthetic data programs
    • Eval-driven training loops
    • Open-weight or closed
  2. 02RETRIEVAL

    Production-grade RAG

    Hybrid retrieval, structured + unstructured corpora, reranking, query rewriting, and citation-faithful generation that survives audit.

    • Vector + lexical + graph
    • Doc-level & chunk-level eval
    • Multi-tenant isolation
  3. 03SAFETY

    Guardrails & evaluation

    Pre- and post-generation policy enforcement, jailbreak resistance, hallucination detection, and continuous offline + online eval.

    • Policy-as-code
    • LLM-as-judge with calibration
    • Red-team programs
  4. 04AGENTS

    Agents & orchestration

    Tool-using agents with deterministic fallbacks, human-in-the-loop checkpoints, and observability you can actually debug.

    • Planner–worker–critic patterns
    • Trace & replay tooling
    • Cost & latency budgets
  5. 05PRODUCT

    AI product development

    From zero to v1 — design, engineering, and applied ML brought together as one team. We ship interfaces humans actually want to use.

    • Concept & UX research
    • Full-stack delivery
    • Design systems & theming
  6. 06PLATFORM

    Implementation & customisation

    Drop AI into the systems you already run — ERP, EHR, CRM, core banking, MES — without a rip-and-replace.

    • SAP / Oracle / Salesforce
    • Epic & Cerner integrations
    • Legacy & mainframe friendly
  7. 07INFRA

    MLOps & AI infrastructure

    Training clusters, inference fleets, gateway routing, prompt & model registries, with zero-trust networking and BYOC options.

    • GPU on-prem or hyperscaler
    • VPC / air-gapped deploys
    • Cost & carbon dashboards
  8. 08GOVERNANCE

    Risk, audit & compliance

    Model cards, data lineage, bias & robustness testing, and EU AI Act / NIST RMF / ISO 42001 readiness baked into delivery.

    • Documentation as code
    • Independent eval harness
    • Regulator-ready artefacts
  9. 09DATA

    Data & knowledge engineering

    Corpus design, ingestion pipelines, entity resolution, and chunking strategies — the unglamorous work that determines whether retrieval actually works.

    • ETL & document parsing
    • Knowledge graph construction
    • Freshness & lineage tracking
  10. 10MULTIMODAL

    Multimodal & document AI

    Vision, audio, OCR, and structured extraction over PDFs, scans, plant imagery, and clinical records — not just text in a chat box.

    • Layout-aware parsing
    • Image & video understanding
    • Structured field extraction

Industries

Five domains. One operating philosophy: ship what survives production.

01 / 05RETAIL & CPG

Conversational commerce, merchandising copilots, demand intelligence.

From category managers asking natural-language questions of a 200-million-row sales cube, to shopper-facing assistants grounded in live inventory and policy — we turn retail's messy data into systems associates actually trust.

  • Personalisation engines on first-party data
  • Catalog enrichment & multilingual content at scale
  • Returns, refunds & CX agents with policy guardrails
  • Forecasting + assortment optimisation
02 / 05FINANCIAL SERVICES

Research copilots, document intelligence, KYC & surveillance.

For banks, insurers, and asset managers operating under heavy supervision. We build systems where every generation can be cited, replayed, and defended — and where model risk management isn't an afterthought.

  • Analyst research & earnings synthesis
  • Credit memo, ISDA & ICAAP automation
  • Trade surveillance & comms monitoring
  • Customer-facing assistants under MRM controls
03 / 05INDUSTRIAL & MANUFACTURING

Operator copilots, predictive maintenance, knowledge capture.

We turn 30 years of tribal knowledge — SOPs, work instructions, incident reports, OEM manuals — into assistants that sit alongside operators on the line and work even when the network drops.

  • Multimodal QA on plant imagery & sensor data
  • Field-service troubleshooting agents
  • Document-grounded SOP & safety assistants
  • Edge-deployable, low-bandwidth optimised
04 / 05DEFENCE & PUBLIC SECTOR

Air-gapped intelligence systems, OSINT triage, doctrine assistants.

Cleared engineers, sovereign deployments, and a discipline around provenance, classification, and chain-of-custody. We build for environments where trust is earned with paperwork as much as code.

  • On-prem / air-gapped LLM stacks
  • OSINT & multilingual document triage
  • Mission & doctrine retrieval assistants
  • Adversarial & red-team hardened
05 / 05HEALTHCARE & LIFE SCIENCES

Clinical documentation, payer ops, biomedical search.

PHI-safe by default. We build assistants for clinicians, coders, and researchers — grounded in guidelines, payer policy, and primary literature — with HIPAA / HITRUST controls baked in from day one.

  • Ambient scribe & coding assist
  • Prior auth & payer-document automation
  • Biomedical retrieval over PubMed + internal
  • De-identification & consent enforcement

How we build

A reference architecture, then everything that real production demands.

Every Grawity engagement starts from the same opinionated backbone — and ends somewhere specific to your data, risk profile, and infrastructure. The diagram is the easy part.

  1. 01
    Discovery & risk framing

    Workshops with the people who will own the system. We surface failure modes, regulatory boundaries, and what "good" looks like before a single token is generated.

  2. 02
    Data & retrieval design

    Corpora, chunking, embeddings, hybrid retrieval, and a baseline eval harness. The retrieval system is the system.

  3. 03
    Model selection & training

    Open-weight or closed, fine-tuned or prompted, single model or routed ensemble — chosen against your eval, not a leaderboard.

  4. 04
    Guardrails & eval-as-CI

    Policy-as-code at input and output, regressions caught on every change, and a golden set the business actually believes in.

  5. 05
    Deploy, observe, iterate

    VPC, on-prem, or hybrid. Tracing, cost, drift, and feedback loops feeding the next training cycle.

01 · INPUT User query · documents · multimodal · structured calls 02 · INPUT GUARDRAILS PII redaction · policy filters · prompt-injection detection 03 · RETRIEVAL LAYER Hybrid search · rerank · graph traversal Vector store · BM25 · knowledge graph · feature store 04 · GENERATION Routed LLMs · fine-tuned adapters · tool use Open-weight · closed · on-prem · planner / worker / critic 05 · OUTPUT GUARDRAILS Citation faithfulness · policy · hallucination scoring 06 · OBSERVE · TRACE · EVAL · RETRAIN

Representative work

The kinds of systems we build — patterns, not press releases.

Illustrative engagements across our domains. Client names, volumes, and metrics are anonymised until we can share them with you directly.

RETAIL—Engagement pattern

Merchandising & category intelligence copilots.

Natural-language access over large sales, stock, and pricing datasets — role-aware, grounded in live inventory and policy, built for teams who need answers in minutes, not days.

  • Hybrid retrieval
  • Role-based access
  • Multi-market rollout
FINANCE—Engagement pattern

Research & document copilots under model risk controls.

Earnings, filings, and internal research with citation-level provenance — deployed inside the client's VPC, aligned with model risk and audit requirements.

  • VPC deployment
  • Full provenance
  • MRM-aligned
DEFENCE—Engagement pattern

Air-gapped doctrine & mission retrieval.

On-prem, sovereign LLM stacks with classification-aware retrieval, role-based access, and guardrails hardened through adversarial testing.

  • Air-gapped
  • Classification tiers
  • Red-team hardened
HEALTHCARE—Engagement pattern

Clinical documentation & ambient scribe systems.

PHI-safe ambient documentation with specialty-tuned templates, payer-aware coding suggestions, and continuous improvement from signed-note feedback.

  • PHI-safe by default
  • Specialty templates
  • Continuous eval loop

Company

A small team. Senior by default. Allergic to slideware.

Grawity is built around a tight bench of staff and principal-level engineers, applied scientists, and product designers — most of whom have shipped large-scale AI inside fintechs, hospitals, factories, hyperscalers, and government.

We deliberately stay small. Every engagement is led by a partner. Every system is debuggable by the people who built it. We say no often.

  • Eval first. If we can't measure it, we won't ship it.
  • Provenance always. Every output should be traceable to its source.
  • Boring infrastructure. The exciting part is what runs on it.
  • Plain language. If we can't explain it to your auditor, we redesign it.

Ready when you are

You don't need another demo.
You need a partner who ships.

Partner-led engagements. Reply within one business day — from someone who will actually build your system.

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