01
Not enough people
People spend too much time on enquiries, data entry and other work that should not require constant manual effort.
AI Agent / LLM / Automation
AI & System Development Movie
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Services
AI & System Development Fix the work that slows you down — by changing the system behind it.
Staff shortages, repetitive work, scattered information, knowledge silos and difficult systems. We combine AI development, AI Agents, RAG, LLMs and cloud AI to build solutions that work in real operations.
We combine AI Agents, LLMs, RAG, APIs, AWS / Azure and other technologies to fit the problem.
YOUR CHALLENGES
Do any of these problems sound familiar?
Before talking about systems or AI, we start with what is actually creating friction in day-to-day work.
02
The same work keeps repeating
Teams repeatedly enter, copy, total and rewrite the same information across spreadsheets, emails and systems.
Generative AI / Workflow / API
03
Information is scattered
Important information is spread across spreadsheets, email, documents and shared folders, making it slow to find.
RAG / Embeddings / Vector DB
04
Knowledge lives with one person
Critical know-how sits with particular employees, making handovers, training and continuity difficult.
Knowledge AI / RAG / LLM
05
Current systems are hard to use
Legacy systems and disconnected tools create duplicate entry, extra checks and unnecessary work.
API / Database / AWS / Azure
06
You want AI, but do not know where to start
You see the potential of generative AI, but it is not clear where it would create real value in your business.
PoC / AWS Bedrock / Azure OpenAI / OpenAI API
FROM PAIN TO IMPROVEMENT
Here is what better can look like.
We apply AI and system engineering to the workflow to reduce friction, make information easier to use and give people more time for work that truly needs them.
01
Enquiry handling
BEFORE
Staff answer the same questions one by one, every day.
AFTER
Routine questions are handled automatically, while cases that need judgement are passed to a person.
Less time on routine replies, more time for valuable work.
AI Agent / RAG / LLM / Tool Use
02
Internal knowledge search
BEFORE
Manuals and documents live in different places, so finding an answer takes too long.
AFTER
Organise the knowledge so employees can ask a question and quickly find the right answer.
Less searching and faster decisions.
RAG / Embeddings / Vector DB / LLM
03
Data entry & reporting
BEFORE
People read emails or spreadsheets and manually re-enter the information elsewhere.
AFTER
Extract the required information and connect it directly to registration and reporting.
Reduce both processing time and input errors.
Generative AI / OCR / API / Workflow
04
Customer & case management
BEFORE
Customer information and activity history are scattered across email, spreadsheets and personal files.
AFTER
Bring the information together so the team can see the current status at a glance.
Reduce dependency on individuals and prevent missed follow-ups.
AI Assist / CRM / API / Database
HOW WE HELP
How Towa AI can help
Starting from the business problem, we combine AI Agents, RAG, LLMs, generative AI, vector databases, APIs, AWS / Azure and other technologies as needed, then build them into usable systems.
01
Reduce enquiry workload
Structure common internal and external questions, automate the first response and route only the right cases to staff.
AI Agent / RAG / LLM / Tool Use
02
Make knowledge easy to find
Bring manuals, policies, product documents and FAQs together so people can find what they need by simply asking.
RAG / Embeddings / Vector DB / LLM
03
Remove repetitive work
Review repetitive entry, transfer, classification, reporting and document tasks, then automate the parts that do not need a person.
Generative AI / OCR / Workflow / API
04
Build systems around the way you work
Design and build customer, case, booking, enquiry, product or member management systems around your actual process.
Web System / Database / AWS / Azure
05
Improve what you already have
Instead of replacing everything, connect and improve the parts that matter while keeping useful existing systems and SaaS tools.
REST API / Webhook / OAuth / SaaS
06
Find the right first step for AI
If you are unsure where AI fits, we map the work, choose a worthwhile use case, validate it on a small scale and then move into full development.
PoC / Prototype / AWS Bedrock / Azure OpenAI / OpenAI API
BUSINESS FIRST
Turn AI technology into systems people can actually use.
Towa AI combines AI Agents, RAG, LLMs and generative AI with web applications, APIs, databases and AWS / Azure cloud platforms, implementing them as systems that run in real operations.
Depending on the use case, we also work with LLMs, vector databases, embeddings, function calling / tool use, MCP, OCR, multimodal AI, AWS Bedrock, Amazon SageMaker, Azure OpenAI and the OpenAI API.
01
Start with the problem
We clarify the business problem, then architect where AI should be used and where conventional system design is more appropriate.
AI Architecture / LLM / Agent Design
02
Change only what needs changing
Keep what already works and improve the highest-impact areas through APIs and cloud integration.
API Integration / AWS / Azure / SaaS
03
Build it into real work
We do not stop at a demo. We integrate AI Agents and RAG with interfaces, data, permissions and operations so the solution can actually be used.
AI Agent / RAG / Monitoring / Security
HOW WE WORK
Clarify the problem first, validate the idea, then build.
We do not assume a large project from day one. We align on goals and priorities, then start with the scope that makes sense.
01
Understand the problem
Map the current workflow, pain points and the tasks consuming the most time.
AI Use Case / Requirements
02
Prioritise
Prioritise based on impact, feasibility, cost, security and expected LLM usage costs.
Feasibility / Security / LLM Cost
03
Validate on a small scale
Where useful, use a PoC or prototype to validate LLM quality, RAG retrieval, usability and impact early.
PoC / Prototype / LLM Evaluation / RAG
04
Design & build
Design and build AI Agents, RAG, APIs, interfaces, data, permissions and cloud architecture around the real operating flow.
AI Agent / RAG / API / AWS / Azure
05
Improve after launch
Use real usage after launch to improve prompts, RAG, model selection, features and operations.
Monitoring / Prompt Tuning / RAG Tuning
WHY TOWA AI
Strong AI & system engineering, all the way to business change.
Business-first thinking
Starting from the business problem, we architect where AI Agents, LLMs, RAG and related technologies should be applied.
AI Consulting / Architecture / LLM
AI and systems together
We combine AI Agents and LLMs with web applications, databases, APIs and admin tools so the result fits real operations.
AI Agent / LLM / RAG / Web / DB / API
Use what you already have
We reuse existing systems and SaaS, adding AI on AWS / Azure and API integrations where they create value.
AWS Bedrock / SageMaker / Azure OpenAI / API
Keep improving
After launch, we keep improving LLM quality, RAG retrieval, logging and cost based on real usage.
Evaluation / Observability / MLOps / Cost
FAQ
Frequently asked questions
Q01 Can we talk even if we have not decided what to build?
A
Yes. Many projects start before a specification exists. If you simply want to reduce a task or improve the way something is managed, we can start by clarifying the problem and priorities.
Q02 What if we are not sure whether AI is the right solution?
A
Absolutely. We separate the parts where AI adds value from the parts better handled by conventional systemisation. We do not force AI into the proposal.
Q03 Can you improve our process without replacing the current system?
A
Yes. We can often improve an existing environment through APIs, data connections or targeted modifications. We do not assume everything needs to be rebuilt.
Q04 Can we test on a small scale before full development?
A
Yes. We can use a PoC or prototype to confirm how the idea works and whether it creates value before moving into full development.
Q05 Can you support and improve the system after launch?
A
Yes. We can continue improving features, AI behaviour, integrations and operations based on how the system is actually used.
Q06 Can you advise on security when internal data is involved?
A
Yes. We review the data involved, access permissions, what may be sent to external AI services and logging requirements, then design an appropriate setup.
START WITH THE PROBLEM
Start with one question: “Can this problem be solved better?”
You do not need a finished specification. From AI development, AI Agents, RAG and LLMs to AI on AWS, we can help choose the technology and define what should be built and how.
