Enterprise knowledge assistant
Answers from your policies, SOPs, contracts and manuals, with citations to the exact source.
Generative AI & LLM solutions
Generative AI grounded in your data. Answers you can trust.
We build enterprise assistants, "talk to your data" experiences and document intelligence that answer from your own sources, respect every user's permissions, cite their sources, and can run privately on your infrastructure.
01Grounded & cited02Permission-aware03Private deployment
What we build
Generative AI that works on your knowledge, not the internet's.
Talk to your data
Plain-English questions over ERP, HR and operational databases, with validated, role-aware queries.
Document intelligence
Summarize, compare and extract from contracts, invoices, reports and forms at scale.
Content & proposal generation
First drafts of proposals, RFP answers, reports and posts in your voice, with human review.
Customer & employee chat
Assistants on your website, portal, Teams or WhatsApp that answer from approved content.
AI inside your applications
Generative features embedded in your existing ERP, CRM or custom apps through APIs.
Live demo
Ask a database a question. Watch the guardrails work.
Pick a question, then switch roles and ask again. The same question gets a different, correctly scoped answer, and restricted data is blocked before it ever reaches the database.
Signed in as Ravi · Human Resources. Pick a question:
Choose a question to see how a governed AI answers it, step by step. Then switch roles and ask again.
Demonstration with sample data, modelled on our governed AI Chat platform. Read the case study.
How it works
Retrieval-augmented generation, engineered for the enterprise.
01
Ingest
Documents and data are cleaned, chunked and indexed, and permissions are kept.
02
Retrieve
Each question pulls only the most relevant passages the user is allowed to see.
03
Ground
The model is instructed to answer only from the retrieved sources.
04
Validate
Outputs are checked: citations, policy rules, and query validation for data answers.
05
Answer & learn
The answer is shown with sources, and feedback improves retrieval over time.
Accuracy & safety
Hallucinations are an engineering problem. We engineer them out.
No single prompt makes an LLM reliable. Independent layers do, each catching a different failure. Read more about our responsible AI approach.
Curated context
A catalog of approved sources, tables and definitions, so the model never guesses.
Validation before action
Generated queries and outputs are checked against rules before they're used.
Permission-aware retrieval
Users only retrieve documents and rows they're entitled to see.
Citations by default
Every answer links back to its sources so people can verify it.
Prompt-injection defence
Instructions hidden in documents or user input are treated as data, not commands.
Honest fallbacks
When the sources don't contain the answer, the assistant says so or asks a question.
Deployment options
Run it where your data rules say it must run.
Managed cloud models
Leading commercial models through enterprise endpoints, with data-retention controls.
Best whenYou want top accuracy quickly
Private cloud
Models hosted in your own cloud tenant on Azure, AWS or Google Cloud.
Best whenData must stay in your cloud boundary
Self-hosted open models
Open-weight models running on your own servers or GPUs, fully offline if needed.
Best whenData must never leave your premises
Proof
All AI case studiesGenerative AI we've built and shipped.
From governed data assistants to content engines with human review.
Governed 'talk to your data' for enterprise HR and operations
Business users ask questions in plain English and get accurate, access-controlled answers from SQL Server, with every query validated before it runs.
80–90%lower LLM token cost per query vs full-schema prompts
7-stageSQL validation before any query runs
Scaling LinkedIn content without losing the brand voice
An AI content engine drafts posts and visuals on schedule, with a human approval gate and engagement data feeding back into the prompts.
80%of drafts, visuals and ideas generated by AI
20%human review for brand accuracy
RAG connects a language model to your own documents and data. For each question, the most relevant passages are retrieved and the model answers from them, with citations, instead of relying on what it memorized during training.
We layer controls: curated sources and schema, permission-aware retrieval, instructions to answer only from sources, validation of outputs and generated queries, and citations so users can verify. When the sources don't contain the answer, the assistant says so.
Yes. Our 'talk to your data' approach turns plain-English questions into validated SQL, checked against approved tables, columns and joins, with row-level access applied before anything runs. Try the demo above.
Yes. We deploy models in your private cloud or on your own servers, including open-weight models that run fully offline.
We're model-agnostic: leading commercial models and open-weight models, chosen per use case for accuracy, cost, latency and data residency.
A focused pilot on one knowledge domain or one database typically takes a few weeks, depending on data preparation and integrations.
Have documents or data your teams struggle to use?
Let's build an assistant your people can trust.
Bring one knowledge domain or one database. We'll show how a grounded, permission-aware assistant would answer your team's real questions.
At Techno Genesis, we’re passionate about crafting digital solutions with the latest technology, ensuring our clients stay ahead and embrace the future with confidence and innovation.
#Together, we shape a brighter tomorrow.
Let’s create a legacy of greatness, together.
Let's Talk
sales@technogenesis.in
Services
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