## Menu-based chatbots

The simplest chatbots do not bother with processing the text typed by the user. Instead, a user can choose from a limited set of predefined “phrases” by pressing the appropriate phrase-button. [Landbot.io](https://landbot.io/) constructor is a good example of such approach. Slash-command Slack bots also fall into this category.

These bots don’t require NLU and the complications it brings, and thus are extremely easy to implement. In many cases, you don’t need to write even a single line of code. There are tools that allow creating such a bot and designing the dialogue flows in visual editors.

Menu-based chatbots are successfully used by a lot of businesses, but they are not nearly as engaging as other types of bots. Still, for basic customer service with simple queries and predefined conversation flows, they provide the best value for the money. Also, they are a great option for a quick test of a market or idea along the lines of lean approach.

Now, let’s step out from the comfort zone of controlled user behaviour into the realm of unrestricted free text input. And here comes…

## Rule-based chatbots

The simplest thing you can do when processing the free text input is to detect keywords and phrase patterns and then to react based on them. Given the complexity and variability of natural language, this approach is very simplistic. Nevertheless, it is impressive how far you can get with it if you need a highly specialised bot for queries with limited and very specific vocabulary.

Rule-based chatbots rely on simple text processing tools (read: regular expressions), and thus can be up and running quickly without any knowledge of modern NLU science. Unfortunately, as the project expands with additional functions and broader vocabulary, a bot becomes too complex to maintain and develop.

Poor scalability coupled with the inability to fully embrace the richness of natural language makes this approach the least recommended. But if you still want to try it, check out [ChatScript](https://github.com/bwilcox-1234/ChatScript).

Finally, we are entering the realm of true NLU. But this does not need to be too hard since you can create…

## Chatbots based on NLU-as-a-Service

Everything is simpler with SaaS. And thanks to Clouds, we have a good selection of SaaS NLU providers. Not surprisingly, most the famous names come from FAMGA:

* [Wit.AI](https://wit.ai/) by Facebook;
* [LUIS](https://www.luis.ai/) by Microsoft;
* [DialogFlow](https://dialogflow.com/) by Google;
* [Lex](https://aws.amazon.com/lex/) by Amazon.

There are some promising startups in the field too, [Recast.AI](https://recast.ai/) and [Craft.AI](http://www.craft.ai/) being just a few worth mentioning.

Most of these services provide APIs for intent classification. Here’s how they work. First, you define a model. The model basically contains a set of intents the user may express while chatting with the bot and some sample utterances the user may use for that (the more the better). Then, you let the service learn on this model. After that, the NLU-as-a-Service will be able to analyse the actual user input in real time and tell you to which intent it most likely corresponds. Unlike a rule-based bot, this service can recognise the intent even if the real user’s message is quite different from what the developers have provisioned.

The actual development process is somewhat more nuanced, and you better entrust it to the experts that understand the concepts behind it. But apart from this, everything is still straightforward, and the project kick-off is as fast as with the rule-based approach. At the same time, NLU-as-a-Service bots scale better as their functionality grows.

Chatbots of this type provide a middle ground between the cost of development and the potential of the bot. NLUaaS gives you good results with interpreting user goals from conversational queries, but that may still be not enough. If you need a universal mechanism for entities recognition, support for complex contexts, ability to nest dialogues, etc., you will want to go with…

## Chatbots with custom NLU stack

If you need more flexibility in the way your NLU works, you have to build your own stack from the open-source, free, or purchased components. You can choose the [Rasa Stack](https://rasa.com/) that is a drop-in replacement for the abovementioned intent classification services.

> **"You will need to roll out your own infrastructure, but for this additional cost you will also get the ability to fine-tune the NLU pipeline to the exact domain you need to get better results. SaaS solutions cannot do that as they are created to work for a broad range of customers", says Andriy Skuratov, R&D Manager at ELEKS** 

Or, you can drop the intent classification altogether and build your bot logic directly around Name Entity Recognition process using, for example, [NLP4J](https://emorynlp.github.io/nlp4j/) from Emory University, or [CoreNLP](https://stanfordnlp.github.io/CoreNLP/) from Stanford—whatever works best for you.

The amazing things such bots can do don’t come for free. Projects of this type tend to take longer, need more infrastructure, and require the [engineers with specific skills](https://eleks.com/services/data-science-services/) that are not so widespread. In general, such projects are more expensive compared to the SaaS approach.

But as a result, you get a more flexible system, NLU that can become incrementally better, higher product quality, and thus the ability to create a more advanced and engaging experience for your users.

So, if you are about quality, this is the way to go. But if you need to take the quality over the top or the problem you are solving is very specific, you will need to…

## Build your NLU from scratch

To do this, you need to involve the experts in the NLU field. They will use the achievements of modern Data Science to create a custom, low-level solution for your problem. Naturally, creating your chatbot from scratch is the most expensive and time-consuming option. We will not go into great detail here as each case is individual and there are no general guidelines. To get a glimpse of the level of tasks solved by this kind of project, we will once again refer you to [our previous article](https://labs.eleks.com/2018/02/how-to-build-nlp-engine-that-wont-screw-up.html).

Now, we will finish our bird’s-eye overview. As you can see, when it comes to creating the chatbot, there is a range of options from the simplest and budget-friendly to the most sophisticated and expensive. [Let us know](https://eleks.com/contact-us/) if you have a choice to make and we will smoothly lead you through the process.

https://labs.eleks.com/


Chatbots are the hot topic. There are lots of articles that explain how to create a chatbot without coding. At the same time in our article, we just recently explored the complexity of Natural Language Understanding (NLU) and how to deal with it

How to Create a Chatbot to Fit Your Needs and Budget

### What’s new?

\
OpenAI's latest release, ChatGPT 4, boasts some impressive new features that are sure to excite tech enthusiasts and developers alike.\
\
1. With the ability to process up to 8 times as many words as the previous version, ChatGPT-4 can provide responses that incorporate greater context and handle larger text inputs. In addition to text inputs, GPT-4 can also handle image, audio and video inputs, paving the way for more sophisticated and diverse interactions with users.

![](https://lh3.googleusercontent.com/Ki811dIDpFiujsCoD7lkL7KqXC_eM5GY9DHnO2yHqhWGPkh7WF6sUpUgCzIAJUWAsstNkf6cYQwau4Fhy4mFU_auuwmbPuRJejDHcMUcKaTZGzRbqIVXP2u88_YrzbmLUpSaEjg6LAYLIk9pwESx4Q)



2. One particularly noteworthy feature of ChatGPT-4 is its ability to build websites from a simple image input. During a recent Developer Livestream, OpenAI demonstrated how the chatbot could take a handwritten sketch of a website and turn it into a fully functioning website that can even generate additional relevant content to fill the site.



3. It's also been [confirmed](https://blogs.bing.com/search/march_2023/Confirmed-the-new-Bing-runs-on-OpenAI%E2%80%99s-GPT-4) that ChatGPT-4 is the model behind the new Bing with ChatGPT. This collaboration marks a significant milestone in the development of natural language processing technology, and could have far-reaching implications for how we interact with search engines and other online tools.



Overall, ChatGPT-4's advanced capabilities and potential for cutting-edge applications make it a compelling tool for developers and tech enthusiasts alike. As we continue to explore the potential of AI and natural language processing, GPT-4 is sure to play a key role in shaping the future of digital interactions.

### How to access?

If you're interested in testing out ChatGPT-4, there are a few important things to know. First and foremost, access to this new technology will be limited at first. OpenAI has stated that only ChatGPT Plus users and developers using the ChatGPT API will be able to use GPT-4 initially.![](https://lh3.googleusercontent.com/yc5sDocp7vBDqKnEFJUiCYb_XMtjhvToM2mrtz6-XxHbjiJmnMikwE4BnDobOtOfyDiygMx5hJ1HtmBSy4QR99eZAZZYVcQ3TwPhi_HY-Bew9iSXV2Vvjrmb_W4Smz5XSdYqYRbDSWlMHstarC2gPw)

It's worth noting that there has been no official word yet on whether the free version of ChatGPT will receive an upgrade to GPT-4 in the future. However, given the significant improvements that GPT-4 brings, it's possible that many users may be interested in upgrading to the Plus version to take advantage of the enhanced capabilities.

### Use cases of ChatGPT-4

Right after the presentation, Conor Grogan, director of crypto trading platform Coinbase, dumped a live Ethereum contract into GPT-4, and it highlighted multiple security vulnerabilities and surface areas where the smart contract could be exploited.![](https://lh6.googleusercontent.com/NgetZZhf20Wc0CHI-vd9os14TsSrz37QL1oxlgVl9xWgmrjHM_GUTO-AkASjf8JsATqOZ0Tzf2ozdjW85UlvNH9EEkDCtM2UYwiHb8EFJ72tzDJfjXEJIInHBZQlU7vdAuKiYbhVbRawcECvgElnyg)

Also GPT-4 has already been put to the test in a [simulated lawyer's bar exam](https://www.forbes.com/sites/johnkoetsier/2023/03/14/gpt-4-beats-90-of-lawyers-trying-to-pass-the-bar/?utm_campaign=socialflowForbesMainTwitter&utm_medium=social&utm_source=ForbesMainTwitter&sh=583e58913027) and performed impressively, landing in the top 10 percent of test takers. This is a major step up from its predecessor, GPT-3.5, which scored in the bottom 10 percent. Additionally, GPT-4 has proven its mettle in other exams, such as SAT Math, where it achieved a score of 700 out of 800.

All in all, the versatility and adaptability of GPT-4 make it a promising tool for various natural language processing tasks, including chatbots, automated news writing, and creative writing. With its expanded word limit, image processing capabilities, and website-building functionality, GPT-4 is set to revolutionize the way developers and tech enthusiasts work with natural language processing technology. As OpenAI continues to improve its algorithms and make its technology more accessible, we can expect to see exciting new applications emerge in the coming years.

On March 14th, OpenAI introduced the new version of ChatGPT, their AI chatbot. The newly released GPT-4 language model has been making waves in the tech community, with many praising its significant improvements over its predecessor, GPT-3.5.  When is GPT-4 coming out? What features will be represented? Continue reading to find it out! 

Exploring the capabilities of ChatGPT 4

The game-changing features of OpenAI's ChatGPT 4

Trading used to be a domain for large-scale investors’ and funds’ activity, but things have changed today. A huge number of retail investors have entered the trading market recently, thus boosting the demand for intuitive, user-friendly trading apps. Automation is another driver for trading apps’ emergence and rapid innovation in the high-tech app world. 

Thus, the stock trading app market grew to [$13.6 billion in 2022](https://www.futuremarketinsights.com/reports/stock-trading-app-market) and is expected to move steadily to $89+ billion in 2032. These figures suggest that retail trading is here to stay, and the market growth of 20%+ a year is a huge business opportunity for forward-looking businesses today. 

So, once you’ve decided to build a robust, functional, and innovative trading app, the choice of the service provider is the key cornerstone of your success. Here’s a list of the top 7 companies I’ve hand-picked for your consideration to give your trading app project a smooth start in 2023.

## **Tips on Finding the Right Trading Software Development Agency**

The task of finding the right software developer for your business is challenging. The market is awash with companies claiming to be the best, while in reality, only a few of them can guarantee top-tier services and excellent software. To choose a genuinely reliable and professional company, you need to focus on the following criteria. 

* **Years in the industry**. Experience is vital when it comes to building trading apps in the modern hi-tech market. An experienced developer with many successful cases can give practical tips on choosing the best technology mix and features. Besides, well-established companies have standardized, smooth workflows, and working with them is more predictable regarding deadlines and quality.  
* **Online reputation**. You should choose companies with a solid online presence and a positive track record for software development. Reliable providers have nothing to conceal, so their clients and staff speak openly on social media and share their positive experiences. 
* **Number of staff**. It’s hard to plan a long-term partnership with a company that only has up to 10 employees or so. You never know what additional features or tech stack you will need in the process of upgrading your app, so it’s better to establish a working relationship with a large team of diversely skilled experts. 
* **Project portfolio**. It’s better to choose a company with a wide portfolio of trading app software projects. This way, you can ensure that the provider indeed has relevant expertise in trading app development and evaluate the real apps’ functionality and quality.
* **Client reviews**. You can check the company’s reputation and reliability by contacting its previous clients indicated on the website as satisfied partners. Checking whether they were indeed satisfied with the partnership and what positive and negative experiences they had will give you a better understanding of what to expect from working with a particular agency.

Once you double-check all the parameters mentioned above, you can be confident in the choice of your trading app development agency. Here are the top 7 companies I’ve selected using the screening checklist above.

## **Top 7 Picks for Trading Software Development**

So, what companies can deliver technically superior service and state-of-the-art trading software solutions in 2023? I sincerely recommend taking a close look at the following options.

### №1. RNDpoint

![](img/top-7-trading-software-development-companies-in-2023_1-scaled.jpg)

RNDpoint has been at the forefront of FinTech software development since 2014. The company employs a large team of experts with in-depth domain-specific expertise and delivers superior software engineering, integration solutions, DevOps, and team augmentation services.

**Year of foundation:** 2014 

**Headquarters:** London, UK 

**Key benefits**: The provider has been specializing in FinTech and banking software for almost a decade. So, it offers state-of-the-art trading software solutions by integrating innovative tools and technologies into the clients’ products. 

**Size:** 250+ employees 

**Major clients:** FICO, Breaking Equity, Loop Wallet, Danske Bank, First Abu Dhabi Bank, Teradata.

**Website:** [www.rndpoint.com](http://www.rndpoint.com/)

### №2. EffectiveSoft

![](img/top-7-trading-software-development-companies-in-2023_3-scaled.jpg)

This development agency has been in the development market for 20+ years and has a huge team of in-house staff exceeding 300 experts. It serves small, medium-sized, and large companies and specializes in tech products for healthcare, finance, and trading industries. The company possesses a Microsoft Gold Application Development certificate and complies with ISO 9001 and ISO / IEC 27001: 2013. 

**Year of foundation:** 2000

**Headquarters:** San Diego, CA 

**Key benefits:** The company has a large customer base and boasts 1,500+ completed projects in various business niches. Its team can create cutting-edge trading app solutions and deliver development, customization, and integration services for stock and crypto trading apps. 

**Size:** 300+ employees 

**Major clients:** Cityindex trading applications, trade execution system EdgeTrade, Cloud Call (cross-platform app as SaaS), BOSS™ instrument console, and Plato (a reporting app). 

**Website:** <https://www.effectivesoft.com/> 

### №3. Empirica

![](img/top-7-trading-software-development-companies-in-2023_4-scaled.jpg)

Empirica is a software development agency specializing in crypto trading and delivering top-notch solutions for crypto market participants. Its services cover crypto market-making software, provision of liquidity in crypto trading platforms, and support of new token listings.  

**Year of foundation:** 2010

**Headquarters:** Turku, Finland 

**Key benefits:** The company is focused on innovation and excellence, so it can deliver effective, trailblazing software for companies entering the crypto industry. Clients of any scale can turn to Empirica for software solutions relating to arbitrage, quantitative trading algorithms, ML and AI solutions for the crypto market, and any other data science, Web3, and blockchain software products. 

**Size:** 25+ employees 

**Major partners:** Coindeal, BitMEX, Bitpanda, Binance, FTX, Coinbase

**Website:** <https://empirica.io/>

### №4. Artezio

![](img/top-7-trading-software-development-companies-in-2023_5-scaled.jpg)

Artezio is a US-based software developer with 20+ years in the industry and 1,000+ award-winning projects. The company hosts a team of over 500 coders to cover its clients’ diverse software needs in the banking, finance, hospitality, and healthcare industries. Its present-day service range covers data analysis solutions, financial trading solutions, currency exchange software, and stocks and equities trading tools.

**Year of foundation:** 2000

**Headquarters:** Princeton, NJ 

**Key benefits:** Artezio has broad expertise in the trading software niche, as the company has dealt with traders and financial organizations. So, it can create custom-tailored trading platforms, mobile trading apps, and various kinds of trading software on demand. 

**Size:** 500+ employees 

**Major clients:** Illumina, InterSystems, RedHat, Xamarin, Sencha, etc. 

**Website:** <https://www.artezio.com/>

### №5. 4IRE

![](img/top-7-trading-software-development-companies-in-2023_2-scaled.jpg)

4IRE is a leading provider of blockchain, FinTech, and banking software development services with a global presence. It is an official integrator of NEAR protocol and partners with Stockholm Digital Finance and Stockholm Sustainable Finance Centre to develop innovative financial solutions.

**Year of foundation:** 2010

**Headquarters:** Tallinn, Estonia

**Key benefits:** 4IRE has a large team of development experts with a solid FinTech background. The company has many finance-related projects in its track record and offers a broad tech stack to design trading apps of any complexity. 

**Size:** 250+ employees 

**Major clients:** Aurora layer-2 protocol for Ethereum, Green Assets Wallet, Maitres, Aztec Protocol, Ondo Finance DeFi protocol. 

**Website:** <https://4irelabs.com/>

### №6. Softvelopers

![](img/top-7-trading-software-development-companies-in-2023_6-scaled.jpg)

Softvelopers has in-depth industry expertise in trading software creation and offers a wide range of AI/ML software solutions, trading robots, and full-scale trading platforms with multiple user-friendly features. The company is a trusted software provider in banking and finance, trading, logistics, and transportation. It also provides innovative software solutions for e-learning, education, and knowledge management businesses. 

**Year of foundation:** 2000

**Headquarters:** Boston, MA 

**Key benefits:** Softvelopers delivers top-tier software services and has a large team of 140+ in-house coders with a broad tech stack covering C++, Java, .NET, Node.js, PHP, and JavaScript. Its experts can create customized trading platforms, analytical solutions for professional traders, automated trading systems, and mobile apps covering Forex, stock exchanges, and cryptocurrencies. 

**Size:** 140+ employees 

**Major clients:** Ship-Ahoy, Digitalchemy, Access, and CityIndex. 

**Website:** <https://www.softvelopers.com/>

### №7. TradingSoft

![](img/top-7-trading-software-development-companies-in-2023_7-scaled.jpg)

The company has a wide range of software solutions for trading businesses, such as physical exchanges, prop shops, brokers, and FCMs. It can create advanced web, mobile, and desktop trading apps that cover all modern feature and functionality demands.

**Year of foundation:** 2012

**Headquarters:** Chicago, IL 

**Key benefits:** TradingSoft can provide for all trading software needs of businesses of all scales. Its experts handle software development (hedging, trading, infrastructure, and trading platforms for physical exchanges), set up the IT infrastructure for trading companies (hardware, colocation, connectivity, cloud, and software infrastructure integrations) and provide 24/7 maintenance and support. 

**Size:** 20+

**Major clients:** Zaner, One Exchange, Typhoon Forex Exchange for Peregrine Financial Group, EDF & Man, PRAXIS. 

**Website:** <https://tradingsoft.com/> 

## Conclusion

As you can see, the market is abundant in trading app developers who can deliver top-notch services without breaking the bank or undermining your deadlines. 

The trading industry is gaining immense popularity and witnessing an influx of retail investors, so the market potential of this niche is still immense. So, you can easily set up a stable revenue stream for your business by launching a safe, functional, and user-friendly trading platform or app. 

Once you’re ready to start the development work, I recommend contacting several companies to check their response speed, communication quality, and the offered pricing. This basic input will guide you in making the final choice and heading to your successful trading app. 

https://4irelabs.com/


If you’ve decided to build a robust, functional, and innovative trading app, the choice of the service provider is the key cornerstone of your success. Here’s a list of the top 7 companies to give your trading app project a smooth start in 2023

Top 7 Trading Software development Companies in 2023

In the demo, which was posted by Google on Twitter for demonstrate the capabilities of their chatbot Bard, which is currently considered the main competitor to ChatGPT Astronomers and astrophysicists, however, immediately noticed a factual error in the chatbot’s response: the AI wrote that the James Webb telescope took the very first pictures of an exoplanet outside the solar system. In fact, the first image of an exoplanet was taken in 2004 using the Very Large Telescope (VLT) complex.

The mistake cost the company dearly: Shares in parent company Alphabet, which owns Google, plunged more than 7%, hurting the company's market value by $100 billion.

Bard’s blunder highlights the challenge for Google as it races to integrate the same AI technology that underpins Microsoft-backed ChatGPT into its core search engine. In trying to keep pace with what some think could be a radical change spurred by conversational AI in how people search online, Google now risks upending its search engine’s reputation for surfacing reliable information.

Like ChatGPT, Bard is built on a large language model, which is trained on vast troves of data online in order to generate compelling responses to user prompts. Experts have long warned that these tools have the potential to spread inaccurate information.

![](img/microsoft_artificial_intelligence_13340.avif)

In an apparent attempt to address that concern, Google previously said Bard would first be opened up to “trusted testers” this week, with plans to make it available to the public in the coming weeks.

> ### **“This highlights the importance of a rigorous testing process, something that we’re kicking off this week with our Trusted Tester program,” a Google spokesperson told CNN in a statement Wednesday about the factual error. “We’ll combine external feedback with our own internal testing to make sure Bard’s responses meet a high bar for quality, safety and groundedness in real-world information.”**

Google unveiled Bard earlier this week as part of an apparent bid to compete with the viral success of ChatGPT, which has been used to generate essays, song lyrics and responses to questions that one might previously have searched for on Google. ChatGPT’s meteoric rise in popularity has reportedly prompted Google’s management to declare a “code red” situation for its search product.

### **Is the world not ready for AI chatbots yet?**

Many experts believe that AI tools are not yet ready for integration into search engines, and therefore you should not rush into this matter.

Carissa Veliz of the University of Oxford believes that this story shows once again that the transition to using AI-powered chatbots to provide web search results is happening too quickly, meaning that the potential for misinformation to spread is huge.


Discover the costly mistake made by Google's Bard Chatbot during its debut, resulting in a staggering $100 billion loss for the company. Learn about the implications and future of AI in our in-depth analysis at The Cymes.

Google's Bard Chatbot Fiasco: $100 Billion Loss After Factual Error in First Demo | The Cymes

CNN: Google’s much-hyped new AI chatbot tool Bard, which has yet to be released to the public, is already being called out for an inaccurate response it produced in a demo this week

Google's Bard chatbot made a factual error during its first demo: The mistake cost the company $100 billion

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