Intelligence,
privately owned.
Helping enterprises move from experimentation to measurable business impact through private, secure Large Language Models (LLMs) and custom RAG pipelines.
STRATEGIC ALIGNMENT
Recognized for engineering excellence.
Forbes India Award
Honored at the Forbes India Small Business Summit 2024 for exceptional technological enablement and digital engineering solutions.
LiveMint 40 Under 40
Visionary leadership and privacy-first artificial intelligence innovation recognized in India's 40 Under 40 list for CEO Gaurav Jaiswal.
NVIDIA Inception Partner
Member of the elite deep-tech program, collaborating on state-of-the-art AI, generative modeling, and computer vision systems.
Microsoft for Startups
Backed by the Microsoft Founders Hub, driving enterprise scalability with advanced Azure cloud and AI infrastructure support.
Clutch Global Recognition
Double-validated as a top-ranked technology pioneer in India for both Top A-Frame Development and Top Immersive Language Experiences.
ISO 27001:2022 Certified
Globally accredited Information Security Management System (ISMS) compliance, validating our enterprise-grade data security.
Generative AI. Driven by Outcomes.
We don't build generic chatbot wrappers. We deploy enterprise-grade Generative AI pipelines mapped to specific business outcomes to drive growth and save operating expenses.
AI for Revenue Growth
- ✓Conversational Qualification (EvaChatBot)
- ✓E-Commerce Transaction Bots
- ✓Dynamic Personalization Engines
Autonomously qualifies inbound leads in real-time, reducing manual SDR response times and boosting checkout conversions by up to 30%.
AI for Operations
- ✓Private RAG Ingest Pipelines
- ✓Automated Contract Analysis
- ✓Dynamic Support Copilots
Instantly queries structured and unstructured datasets, cutting internal knowledge search latency and support ticket volume by up to 60%.
AI for Leadership
- ✓Executive Executive Summarizers
- ✓Scenario-Modeling Copilots
- ✓Observed Risk Monitoring
Aggregates complex multi-source reports into structured executive briefs with full citations, allowing for rapid, data-grounded strategic planning.
A basic API wrapper is not an enterprise solution.
Simply plugging ChatGPT into your corporate database is a massive security risk and guarantees hallucinations. Enterprise GenAI requires strict control over the knowledge base and the model weights.
Public API Wrappers
- ✕
Corporate Data Leakage
Sending proprietary financial documents or source code to public LLM APIs exposes you to IP theft and regulatory violations.
- ✕
Uncontrolled Hallucinations
Standard models guess answers based on broad internet data, confidently presenting incorrect facts to your employees or customers.
- ✕
Vendor Lock-in
Relying entirely on a closed ecosystem means your business is subject to unexpected price hikes, model deprecations, and API outages.
Enterprise RAG Architectures
- ✓
Zero-Egress Deployments
We deploy powerful open-weight models (like Llama 3) directly into your secure VPC or on-premise hardware. Data never leaves the building.
- ✓
Retrieval-Augmented Generation
The AI is mathematically forced to cite its sources from your internal Vector Database. If the answer isn't in your docs, the AI says "I don't know."
- ✓
Model Agnostic
We build abstraction layers allowing you to hot-swap LLMs as new open-source models are released, ensuring you always have the best-in-class AI.
Unlock your trapped corporate knowledge.
Your employees spend 20% of their day searching for internal information. Generative AI eliminates this search time entirely, serving exact, cited answers instantly.
Automating Level 1 internal IT and HR support via highly accurate conversational agents.
Turning massive, unsearchable PDF archives into instant conversational intelligence.
Your proprietary data is never used to train external models. Absolute IP protection.
Multi-lingual AI agents providing continuous support to your global workforce and clients.
Generative AI Across Sectors.
We don't build generic AI wrapper APIs. We engineer **vertical-specific Large Language Model architectures** that fit the unique data schemas and compliance boundaries of your industry.
Healthcare & Life Sciences
We deploy private LLMs that ingest medical literature and clinical records under strict sovereign data policies. Our generative pipelines automate patient triage summarization and clinical trial matching, utilizing zero-egress RAG architectures that prevent sensitive data leaks.
Financial Services & FinTech
Our Generative AI systems automate financial report auditing, summarize complex tax updates (MyStartup CFO), and draft compliance briefs. We secure training weights and vector databases, preventing proprietary investment data from leaking into public domain models.
Education & EdTech
We engineer Socratic learning agents (Qennex) that guide students through problem-solving steps without directly giving answers. Our models process student session histories to adapt tutoring styles and generate personalized exercises in real-time.
Retail & E-commerce
We deploy conversational shopping copilots that help users discover products via natural language search. The models extract features from product tables and review lists, generating dynamic, personalized summaries of product specifications.
Logistics & Supply Chain
Our AI copilots (Godide AI) process unstructured operational manuals, carrier rates, and route databases. Operators query the system in natural language to instantly receive route optimization instructions and dynamic contingency protocols.
Enterprise SaaS & B2B
We build embedded AI copilots directly into B2B software architectures. Users query internal databases via conversational SQL gateways, generate structured reports, and automate customer support ticket triage with up to 60% resolution rates.
Production Generative AI.
We deploy fully custom software interfaces, not just API connectors. Look under the hood of our live deployed client Generative AI systems.
EvaChatBot — Advisory Agent
Built a conversational advisory system that queries private corporate tax and ledger data to qualify leads and provide basic advisory services without sending data to public clouds.
Autonomously qualifies 200+ leads/month while strictly shielding client financial files.
Generative AI in Production.
From secure financial analysis to personalized education, we build custom LLM architectures that deliver measurable business outcomes.
CFOs and financial analysts were spending hours manually digging through massive, unstructured financial ledgers, tax codes, and historical reports to answer basic compliance and forecasting questions.
We engineered a highly secure, finance-specific Retrieval-Augmented Generation (RAG) pipeline. We vectorized decades of tax law and private ledger data into a Pinecone vector database. The custom LLM agent acts as a conversational interface, retrieving exact financial clauses and citing its sources, reducing research time from hours to seconds while maintaining strict GDPR and data security protocols.
The Business Case for Enterprise GenAI.
We understand that deploying Large Language Models (LLMs) requires strict cost-containment, absolute data privacy, and clean system integrations.
For the CFO
We eliminate licensing and infrastructure inflation. We build milestone-driven GenAI platforms with predictable hosting costs.
- Viability AuditWeek 1-2
- RAG Prototype MVPWeek 3-8
- Enterprise LaunchWeek 9-12
For the CTO
Deploy LLMs securely. Our Dockerized RAG pipelines connect via clean REST/FastAPI endpoints to integrate with your existing monoliths.
Containers orchestrated via Kubernetes with clean semantic caching (Redis).
Support for cloud-agnostic GPUs (AWS Bedrock, Azure, or private server nodes).
High-throughput token serving via vLLM and TensorRT runtimes.
For the CISO
We solve the data egress challenge. Your proprietary corporate IP never trains public models.
PII tokenization and hashing in the ingestion ETL layer (GDPR compliant).
Zero-Data Retention integrations and private VPC deployments.
Llama-Guard middleware preventing prompt injection and adversarial attacks.
The GenAI Delivery Framework.
We don't build in a vacuum. We accelerate enterprise generative deployments using our 12-week structured framework and pre-engineered software components.
Discovery
Knowledge Auditing. We review data files (PDFs, docs, databases) to assess structure quality and PII compliance risk.
Design
Model & Vector Scoping. Choosing base LLMs (GPT-4 vs open-source Llama-3) and mapping RAG embeddings database.
Prototype
Baseline RAG Deployments. Engineering vector search algorithms and initial prompting guardrails to validate outputs.
Production
VPC Orchestration. Containerizing models in Docker, setting up API endpoints (FastAPI), and integrating frontends.
Optimization
Latency & Guardrails. Quantizing weights to lower memory costs and finalizing model drift telemetry pipelines.
One AI Chat
A pre-engineered private LLM chat interface template. Connects securely to Pinecone/pgvector, bypassing conversational UI development to save up to 4 weeks of engineering time.
RAG Sync
Dynamic document chunking and indexing scheduler. Automatically processes new PDF/SQL documents and embeds them into vector databases on custom cron schedules.
Llama-Guard Wrapper
A pre-built middleware layer that intercept prompts. Protects models against jailbreaks, prompt injections, and sensitive PII leaks out-of-the-box.
The Enterprise LLM Stack.
We don't just prompt existing models. We build the full-stack infrastructure required to securely integrate Generative AI into your enterprise.
Retrieval-Augmented Generation
We prevent AI hallucinations by grounding the model in your enterprise data. When a user asks a question, the system first retrieves the exact internal document, and the LLM is mathematically constrained to answer only based on that retrieved context.
Strict AI Governance.
Enterprise Generative AI requires guardrails. We engineer systems that enforce strict data access rules, prevent prompt injection attacks, and log every token generated for complete auditability.
RBAC-Aware Retrieval
Not everyone should be able to ask the AI about executive salaries. Our RAG pipelines integrate directly with your IAM (Okta, Active Directory) so the AI only returns information the specific user is authorized to see.
Red Teaming & Security
We deploy strict input/output filter networks that sanitize prompts for injection attacks (jailbreaks) and scrub responses to prevent the accidental leakage of PII or sensitive corporate data.
LLMOps Telemetry
Every prompt and generated token is logged into observability dashboards (like LangSmith or Datadog). We track latency, token cost, user feedback, and semantic drift to maintain the health of the LLM pipeline.
INSTITUTIONAL TRUST // GLOBAL FOOTPRINT
Delivering complex software
for ambitious organizations.
A decade of institutional engineering. Since 2016, Kraftors has been the silent engine behind mission-critical systems. We don't build vaporware; we build for the next 10 years.
Sovereign validation
from industry leaders.
E-Commerce Platform Migration
Successfully migrated their e-commerce portal from .NET to Magento 2, providing continuous management and scaling for over 6 years.
Imtiaz Sayed
Owner, Oxshott Collections
AI Sleep Monitoring Platform
Built an intelligent, privacy-first sleep monitoring solution powered by real-time data and machine learning.
Shadi Abu Hayyah
CEO & Founder, Continual Sleep App
All-in-One AI Platform
Developed a category-based generative AI platform eliminating the need for multiple AI subscriptions.
Prasad Kale
Founder, Kaletech Private Limited
Ed-Tech Platform Success
Designed a user-friendly website allowing students to easily log in and register for various courses and workshops.
Tushar Chetwani
Author & Memory Trainer, Memory Infinite
Media Apps & Reader Engagement
Partnered to build engaging applications for readers during Covid, including large-scale platforms like the All India Memory Test.
Alok Sanwal
COO, Dainik Jagran - inext
Strategic Tech Partnership
A strong collaborative partnership executing multiple complex projects, from e-commerce platform builds to full-scale migrations.
Shubhra Shrivastava
CEO, Digiprima Technologies
Frequently Asked Questions
Clear answers about LLM security, RAG architecture, and deployment.
No. If you use public, free versions of ChatGPT, your data can be used for training. However, we deploy Enterprise API tiers (which have strict Zero Data Retention agreements) or we deploy open-weight models (like Llama 3) entirely within your own Virtual Private Cloud (VPC), ensuring zero data egress.
RAG is an architecture that connects an LLM to your specific corporate data (PDFs, databases, code). When you ask a question, the system first retrieves the relevant internal document, and forces the LLM to read ONLY that document to formulate its answer, drastically reducing hallucinations.
We prevent hallucinations using strict RAG implementations, low-temperature prompt engineering, and 'citation forcing', where the AI is programmatically required to cite the exact source document for every claim it makes. If it cannot find the source, it is instructed to reply 'I don't know'.
For 90% of enterprise use cases (like querying internal documents or customer support), RAG is faster, cheaper, and more accurate. Fine-tuning is only recommended if you need the AI to learn a highly specific proprietary language, syntax, or tone of voice.
Standard chatbots just answer questions. We build 'Agents' using Function Calling. This means the AI can be granted permission to trigger APIs, meaning it can update a Salesforce record, query a SQL database, or send an email on your behalf based on a natural language command.
We implement Role-Based Access Control (RBAC) at the retrieval layer. If an intern asks about the CEO's salary, the Vector Database checks their IAM permissions. Since they don't have clearance, the document is never retrieved, and the LLM literally cannot answer the question.
It depends on the architecture. Using enterprise APIs (like OpenAI/Anthropic) costs fractions of a cent per query. Hosting your own open-source model locally requires renting GPU instances (e.g., AWS EC2 g5 instances), which carries a fixed monthly infrastructure cost.
A proof-of-concept RAG system connected to a subset of your data can typically be engineered and deployed in 4 to 6 weeks.
Ready to build your private AI?
Stop risking your corporate data on public APIs. Let our AI engineers architect a secure, hallucination-free RAG pipeline connected directly to your enterprise knowledge base.
Book an AI Architecture Session