Smart search
Users type the way they think — "cheap waterproof shoes for trekking" — and get the right results, even when those exact words appear nowhere in your catalogue. Synonyms, spelling and intent handled.
AI Services · Integrations
Make your product feel intelligent
Smart search that understands intent, summaries of documents nobody has time to read, recommendations that actually fit, question-answering over your own content, and voice interfaces — added to the website, app or internal tools you already run. No rip-and-replace.
Smart search
Summaries
Recommendations
Q&A over your content
Voice interfaces
Added to your stack
Measured & guarded
Graceful degradation
Summarisation
Contracts, reports, threads and long PDFs reduced to the points that matter — with pointers back to the source so nobody has to trust a summary blindly.
Recommendations
Products, content or next actions suggested from behaviour and context — on the homepage, in the cart, in the dashboard — with a plain fallback when data is thin.
Document question-answering
Ask your own content questions in plain language — policies, manuals, product docs, case files — and get answers cited to the paragraph they came from.
Voice interfaces
Speak a query, get a spoken answer — for hands-free scenarios, IVR modernisation, or accessibility. Built with clear turn-taking and honest "I don't know" behaviour.
Something adjacent?
Classification, extraction, routing, agents inside internal tools — if it fits your product and the data supports it, we will scope it honestly, including when the answer is "not yet".
People find things faster
Search that understands intent cuts the dead-end sessions where visitors leave empty-handed.
Content gets consumed
Summaries and answers surface the value buried in documents your team writes and nobody reads.
Relevant suggestions sell
Recommendations that fit raise basket size without raising ad spend.
Support load shifts left
Document Q&A answers the repeat questions before they reach a human inbox.
Your product stands apart
In a market where everyone claims AI, a feature that demonstrably works is the differentiator.
Built to be extended
Evaluation harnesses and clean integration points mean the second AI feature costs far less than the first.
Golden test sets from your data
Before launch we build a representative test set and score the feature against it — and re-score on every change, so improvements are facts rather than feelings.
Scoped access and honest limits
Answers are limited to sources you allow; the system says "I don't know" instead of inventing; prompts and outputs are logged for review.
Your data's boundaries are respected
Retention, residency and model-provider choices are set deliberately — including self-hosted options where data cannot leave your environment. Personal data handling maps to your DPDP/GDPR duties.
Degradation is designed, not accidental
If the model times out or confidence drops, users get keyword search, static content or a human path — never a blank screen.
AI inside
No. Integrations are added to what you already have — through APIs, embedded components or a search index alongside your data. Nothing is re-platformed.
The one that fits the job and your constraints — hosted frontier APIs for quality and speed, open models self-hosted where data must not leave your environment. The choice is made with you and documented.
We build a golden test set from your real data, score the feature against it before launch, and re-score on every change. You get the numbers, not a demo that behaved itself.
Guardrails keep it contained: answers cite sources or say "I don't know", confidence thresholds route uncertainty to humans, and graceful fallbacks return the old behaviour. Every output is logged for review.
Data boundaries are part of design: retention and residency settings, minimal context sent, and self-hosted options where data cannot leave your environment. Personal data is mapped against your DPDP/GDPR obligations.
A focused feature is usually live within a few weeks; multi-surface work with voice interfaces takes longer. Scope and timeline are fixed in the proposal before building starts.
One-time integration and evaluation work, plus model and hosting usage billed at actual cost. We quote a fixed price after seeing your data and agreeing the success metric.
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“CyberSwipe built the full stack behind Youvabot — CRM, WhatsApp bot, calling bot and the Android app, and everything has been great.”
“CyberSwipe developed the complete Kingermart platform — e-commerce website, app and everything behind them, and everything has been great.”