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Also serving Madras
Chennai firms hold years of inspection records, support tickets and patient files; custom AI turns that history into answers, built around each firm's own data.
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Photo: SlowPhoton · CC BY-SA 4.0, cropped · via Wikimedia Commons
Trusted by 200+ organisations across India & overseas — including
Rarely, and seldom needed. Most business problems are solved better by combining a proven language model with retrieval from your data and sensible guardrails. Where a smaller fine-tuned model fits better, for example classification at volume, we use that and explain why.
By grounding answers in retrieved source text, showing the source to the user, restricting the assistant to its domain, testing against a fixed question set, and routing low-confidence cases to a person. It will not be perfect, so review is designed in.
Current language models handle Tamil text reasonably well, and mixed Tamil-English even better than a few years ago. We test on your own samples before promising anything, since handwriting, old scans and dialect affect results.
After a first conversation about the use case, the data behind it and the accuracy you need, we agree the scope and send you a written quotation. The price, the deliverables and the timeline are fixed against that scope before any work starts, so nothing grows without your sign-off.
You speak to someone who does this work, not a call centre. They ask about the decision or task you want AI to handle, the data behind it and the result you need. If it looks like a fit, we agree the scope and put it in writing, with the timeline, before any work starts. If it does not, we tell you.
Off-the-shelf AI tools know nothing about your parts, your contracts or your patients. That is the limit many Chennai companies reach after a few months of trying chat assistants at work: the answers sound confident and are wrong in the details that matter. The value lies in AI grounded in your own documents and records, with access rules that match your organisation.
As an AI development company we build that layer: assistants that answer from your manuals, SOPs and ERP data, document handling that reads and classifies incoming papers, and automation that acts on the result. We use established language models, add retrieval from your data, and design human review into any step where an error would be expensive. Projects begin with a narrow pilot and measurable targets.
Case studies
Connect N Cabs Tours & Travels Pvt. Ltd.
Connect N Cabs — A Custom Travel ERP That Lifted Fleet Utilisation 35%
Della Fashions
Della Fashions — ERPNext POS Made Checkout 60% Faster Across Every Outlet
Dumas Bakes N Meals Private Limited
Dumas Bakes N Meals — ERPNext Lifted On-Time Deliveries by Over 40%
An auto-component plant may hold decades of customer complaints, corrective-action reports and drawings across shared drives. When a similar defect appears, nobody finds the earlier fix. A retrieval assistant lets a quality engineer ask in plain language and get the earlier report, with its source shown.
Software firms along OMR resolve tickets using whatever the engineer on shift remembers. An assistant grounded in past tickets, release notes and documentation drafts the reply and cites where it came from, which steadies the quality across shifts.
Staff paste patient details or contract terms into public chat tools because nothing approved exists. A private assistant with logging, masking and role-based access gives them the help they want without the data leaving the boundaries the organisation has set.
An example
At a machining unit in the Ambattur belt, a customer complaint arrives on Tuesday about a bore going out of tolerance on a bracket. The quality engineer opens the assistant and asks whether this part, or its family, has had a similar rejection before. Within moments it returns two corrective-action reports from years back, a drawing revision note and the control plan clause that was changed, each with a link to the original file on the company's own server. She reads the earlier root cause, checks the current fixture against it, and drafts the customer's reply with the history attached. The plant head, reviewing the draft, sees where every statement came from before he signs it. Nothing about the part or the customer has left the company's network.
We run AI development from Kochi, with your data held where you decide: your cloud, your server or an agreed secure environment. An opening workshop in Chennai, or Madras if your letterhead still says so, fixes the use case, the success measure and the data rules. After the pilot, we visit again to train users and tune the system against real questions.
Discovery and feasibility. Use cases ranked by payback and data readiness: a plan, not a pitch.
Pilot on real data. The first use case, measured for accuracy and time saved against your manual baseline.
Human review loop. Your team validates outputs while we tune to your threshold.
Production hardening. Audit logs, fallback paths, monitoring and access controls.
Scale and integrate. Rolled into your web and mobile apps and your dashboards.
The scope and timeline are agreed in writing before work starts.
Automotive & auto components
Assistants over quality records, control plans and customer manuals; reading of supplier certificates and inspection reports; and summaries of schedule and delivery performance drawn from the ERP for the morning production meeting.
IT & software services
Ticket triage and reply drafting, internal knowledge assistants for engineers, proposal and RFP answer libraries, and AI features built into the products Chennai software firms sell, where we work as an extension of the product team.
Healthcare & medical tourism
Assistants that help coordinators answer overseas patient queries from approved content, summarisation of referral records for the treating team, and claim-document support, always with clinical sign-off before anything is sent.
Indian Institute of Technology Madrasinstitution
central technical institute (1959) at Adyar/Guindy; ranked first overall in NIRF for several years; runs the IIT Madras Research Park at Taramani, India's first university-based research park
Home to India's first university-based research park at Taramani. The AI talent and start-ups around it set the standard a Chennai buyer will compare any vendor against.
Source: en.wikipedia.orgTICEL Bio Park, Taramanipark
State biotechnology park at Taramani housing biotech firms and laboratories, named in the district profile alongside TIDEL Park.
The state biotechnology park housing laboratories and biotech firms. Research documentation, assay records and regulatory filings are exactly the dense, private corpus that retrieval-based assistants suit.
Source: cdn.s3waas.gov.inTamil Nadu Dr. M.G.R. Medical Universityinstitution
the state medical university, headquartered in Chennai
The state medical university, headquartered in the city. Its affiliated hospitals hold referral records and discharge summaries that AI can summarise for clinicians, under their sign-off.
Source: en.wikipedia.orgPlaces and organisations are named for local context only. Acube Innovations is not affiliated with or endorsed by them.
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Kochi (Kadavanthra & Infopark) · Thiruvananthapuram · across India & overseas · In business since 2011