AI development and integration
AI features that take real work off your team’s plate, built into your existing software and measured against a clear goal.
- Founder-ledyou work with the people who build it
- Pune-basedserving clients across India and abroad
- Googlefind us on Google (opens in a new tab)
Most businesses do not need a research lab. They need a few well-chosen AI features that save hours every week: answering routine customer questions, pulling data out of invoices and forms, finding the right document in seconds, drafting replies for a person to approve, or flagging which leads and orders need attention first.
We start with the task, not the model. Together we pick a job that is repetitive, measurable and worth automating, check that you have the data it needs, and agree how success will be measured before anything is built. Then we integrate the right tool into your software, whether that is a hosted language model through an API, an open model from Hugging Face, or a custom model trained in Python with PyTorch or TensorFlow.
AI features fail in production when nobody plans for wrong answers. We design human review where mistakes are costly, keep sensitive data out of places it should not go, log what the system does, and give you a way to measure accuracy over time.
What we build
AI assistants and chatbots
Assistants that answer questions from your own documents, policies and product data, with hand-off to a person when needed.
Document and data extraction
Reading invoices, forms, contracts and ID documents to pull out structured data for review and entry.
Smart search and recommendations
Search that understands meaning rather than exact keywords, and recommendations based on behaviour or content.
Predictive analytics
Models that forecast demand, flag risk or score leads using your historical data.
AI inside existing software
Adding summarisation, drafting, classification or translation to tools your team already uses.
Built for teams at every stage
- Startups
- AI features that make your product stand out, built on reliable foundations rather than a demo.
- SMEs
- Practical automation of repetitive tasks such as data entry, customer queries and report writing.
- Enterprises
- Governed AI pilots with clear metrics, access controls and a path to production.
- Public sector
- Translation, document processing and search for large, multilingual records, with human review built in.
Tech stack
- Python
- OpenAI API
- Hugging Face
- PyTorch
- TensorFlow
- Node.js
- Next.js
- AWS
How the project runs
We agree one business task, the data it needs and a measurable target, then build a small proof of concept on your real data. If it meets the target, we integrate it into your software with review steps, logging and cost controls. After launch we track accuracy and usage and tune the system as your data changes.
See the full Scriptiqo Delivery System →Frequently asked questions
Where should a business start with AI?
With one repetitive task that takes real staff time and has a clear right answer, such as extracting data from documents or answering common questions. Starting small gives you a measurable result quickly and shows where AI is worth more investment.
Do we need to train our own AI model?
Usually not. Hosted language models and open models cover most business tasks when combined with your own data. Custom training makes sense for specialised predictions where you have enough historical data.
Is our data safe when using AI services?
We choose providers and settings that do not use your data for training, send only the data a task needs, mask sensitive fields where possible, and can run open models on your own infrastructure when data must not leave it.
What if the AI gives a wrong answer?
We design for it. Costly decisions get a human review step, answers are grounded in your own documents, and every interaction is logged so errors can be found and corrected.
How do you measure whether it works?
Before building, we agree a metric such as time saved per document, accuracy against a checked sample, or share of questions answered without hand-off. The proof of concept is judged against that metric.
Can you add AI to our existing software?
Yes. Most of our AI work is integration: adding a feature to software you already use, through its API or a small service alongside it.
What does an AI feature cost to run?
Running costs depend on how often the feature is used and which model it calls. We estimate this during the proof of concept, add caching and limits to keep it predictable, and report usage so there are no surprises on your bill.
Tell us about your project
Share a few lines about what you need. A founder reads every brief and replies within 4 business hours.
Prefer to talk? See all contact options.