Tech
Open-Source vs. Proprietary Machine Learning Solutions: Which One is Right for You
The code for open AI models is openly accessible, enabling anybody to view and alter the model. Although this method fosters greater collaboration and transparency, it may result in fewer updates and less robust data security. Machine learning solutions are expected to grow from $26.03 billion in 2023 to $225.91 billion by 2030, at a CAGR of 36.2%. Although open-source AI models are usually free, additional features or support may incur fees.
The customizability and collaboration potential of closed-source AI models are limited by their proprietary code, which is exclusive to the AI development company. Though updates are usually frequent, security is marginally higher because it’s maintained internally. Such an approach results in minimal transparency and limited insight into data handling procedures. Licensing and access fees are nearly invariably associated with closed-source AI models.
Despite their significant differences, each solution still has benefits and drawbacks. Knowing these will enable you to choose the strategy that best suits your company’s requirements.
Open-Source AI Models: What Are They?
Open-source AI models are freely and publicly available for developers to utilize for various tasks.
A good example of an open-source AI model is GPT-Neo. This model is comparable to ChatGPT, which can process and produce text that appears human. GPT-Neo, which is based on open-source code, is a step in the direction of increasing accessibility to sophisticated AI technologies.
Another excellent example is OpenAI’s CLIP, an open-source AI model that links text and images to facilitate tasks like classification and zero-shot learning.
Proprietary AI Models: What Are They?
Systems that are proprietary and maintain the confidentiality of their code are known as closed-source models. An enterprise AI development company that develops closed-source AI models provides greater control over the system by limiting access to the underlying code.
GPT-4, a language model with sophisticated natural language interpretation and generation capabilities, is the most well-known closed-source AI model.
Gemini is yet another excellent example. Google created this AI model to compete with OpenAI’s GPT-4 and other models that can produce text that looks human. It aims to provide people worldwide with strong and adaptable machine learning solutions.
Essential Things for Businesses to Know About Open-Source vs. Proprietary Models
The next thing to think about is whether to use proprietary or open-source models. The following crucial elements from the field should be kept in mind:
Quick Start, Long-Term Trade-offs with Proprietary Models
Proprietary models accessed via APIs provide enterprise-level support and a faster time to market. These machine-learning solutions are perfect for companies that want to implement AI quickly without requiring much in-house knowledge.
Regular updates and support: The makers of closed AI systems provide regular updates and committed support, which guarantees dependability.
Increased security: A more controlled environment results from maintaining the confidentiality of the AI model’s code.
Simplified deployment: Closed-source solutions often include thorough documentation and an intuitive interface that facilitates and expedites the integration process.
Quality assurance: By maintaining quality control, developers make sure the model satisfies industry requirements.
But as businesses grow, it becomes clear that proprietary models have limitations:
Data privacy: Sending private information to other companies is frequently necessary for customization, which raises security concerns.
Prices: Pay-per-use pricing may seem alluring initially, but as AI adoption increases, the prices may soon skyrocket.
Vendor Dependency: Companies rely on outside infrastructure for dependability and uptime, which might provide operational risks if a vendor goes down.
Open-source models: Cost-effectiveness, flexibility, and control
Conversely, open-source models provide companies with complete command over their AI setup. Businesses can customize AI performance to meet particular requirements by leveraging confidential data to refine these models without disclosing private information to third parties.
Customization: By allowing for extensive customization, open-source models can be improved to better suit applications unique to a particular industry.
Speed: Because the models are adaptable, they can also be optimized based on system specifications and latency.
Cost-effectiveness: Businesses can avoid the rising inference expenses linked to usage-based proprietary models by implementing models on-premises.
Flexibility: Open-source models provide complete scalability at the business’s pace and may be used on any infrastructure, including cloud, hybrid, and on-premises settings.
Ultimately, open-source models’ strength lies in their versatility rather than only their affordability or ease of use. In the long run, firms can innovate more quickly and more affordably by investing in fine-tuning with private data that supports strategic objectives.
But there are drawbacks to open-source as well:
Orchestration at Scale: Because open-source AI models are dynamic, expanding your AI footprint frequently calls for complex orchestration. Policies and cluster-optimized resource allocation are necessary for managing numerous models across teams and hardware infrastructures.
Upfront Investment: Although open-source approaches are frequently free, companies may have to pay upfront to build the required knowledge and infrastructure.
Considerations for Licensing: Commercial use of open-source AI models isn’t necessarily free. Some deployments, like Mistral AI’s, have unique licensing that must be paid for. Before use, always review the licensing terms.
Numerous tools and solutions, both commercial and open-source, have been developed to address these issues and make using open-source models easier.
Choosing Between Open-Source and Proprietary Machine Learning Solutions
Now that we are better aware of the benefits and drawbacks of both worlds, let’s examine the crucial issues and factors that genuinely count when making a decision:
“So, which model should I choose?”
You can’t just choose the right model off the shelf. Focus on trying several models on your data rather than looking for the ideal fit. Compare the outcomes to determine which one best suits your use case. Hugging Faces and other public leaderboards are excellent places to assess models for various tasks. To find out which machine learning solutions work best for your particular requirements, it’s crucial to establish internal benchmarks based on your data.
The Myth of “Bigger is Better”: The Significance of Fine-Tuning
There is a widespread misperception that larger models invariably perform better. On the other hand, LLaMA-3 405B and other basic models perform various functions without specialization. When tailored for specific use cases, like processing legal documents or interpreting financial reports, smaller models—like LLaMA-3 8B—often perform better than larger ones. How effectively the model fits your business demands is more important than its size.
Personalization: The Secret to Successful AI
To elaborate on the last point, fine-tuning turns the basic models from generalists into specialists who perform better in specific domains by training them on domain-specific data. This enables organizations to derive insights from their data helpfully.
A basic AI model, for instance, may comprehend plain language, but unless you customize it using your unique data, it won’t be proficient in legalese or financial analysis. AI gives you a competitive edge in this customization, enabling you to automate processes, enhance decision-making, and spur innovation in the most important ways for your company.
Conclusion
Open-source models provide a clear approach for businesses seeking more control, flexibility, and cost-effectiveness. In contrast to proprietary models, which frequently have restricted customization options, significant scaling costs, and a reliance on external infrastructure, open-source solutions return control to you. Machine learning solutions may be refined and deployed on your terms, whether in a hybrid arrangement, on-premises, or in the cloud, giving you the flexibility to innovate at your speed.
Although the question “Which model should I choose?” may not have a definitive answer, choosing the right AI development company can give you a better idea of where to seek guidance when making these choices.
Remote troubleshooting used to be a niche requirement. Today, it’s core to keeping a distributed workforce productive and customers happy. Whether an employee is working in a co-working space across town or a customer is stranded halfway around the world, they expect IT to swoop in, diagnose the problem, and restore service with minimal disruption. That expectation forces support teams to adopt tools that go far beyond simple screen sharing. Modern remote-support platforms must deliver enterprise-grade security, near-instant connectivity, cross-platform versatility, and the analytics managers need to fine-tune service levels.
This in-depth guide explores why remote-support software matters, which features drive real productivity gains, and how four leading products-TeamViewer, AnyDesk, Zoho Assist, and Splashtop SOS-compare in day-to-day use. By the end, you’ll be able to map your own environment’s needs to a solution that accelerates ticket resolution while safeguarding sensitive data.
Why Remote Support Software Matters
The more geographically dispersed your workforce, the harder it is to keep devices patched, applications humming, and end users satisfied. Throw in the growth of SaaS logins, personal laptops, and mobile endpoints, and traditional on-premises help-desk toolkits buckle under the strain. Purpose-built remote-support software counters these challenges in three ways:
- Speed – A technician can join a session within seconds-often with a single code-reducing mean time to resolution (MTTR) and slashing costly downtime.
- Coverage – The same console can reach Windows servers in a data center, a macOS designer workstation, an Android tablet in a warehouse, or an IoT sensor hanging off a production line.
- Security & Compliance – Robust encryption, granular roles, and immutable logs help organizations satisfy controls in frameworks such as ISO 27001, HIPAA, and PCI DSS.
Analysts at Gartner note that high-performing support desks now resolve 40 % of hardware and 70% of software tickets remotely, saving up to $200 per incident in travel and lost productivity costs.
Key Features That Drive Productivity
Not every vendor checks the same boxes, but truly impactful platforms share several foundational capabilities:
- Instant Connection – Unattended agents for managed devices and one-time codes for ad-hoc sessions eliminate lengthy pre-configuration.
- Cross-Platform Reach – Technicians can pivot from a Windows desktop to a Linux server or an iPhone without juggling plug-ins.
- Secure File Transfer – Drag-and-drop patches, logs, or configuration files directly through the encrypted tunnel.
- Multi-Session Handling – Power users can juggle multiple open sessions, chat with different employees, or shadow a colleague’s screen for training.
- End-to-End Security – AES-256 encryption, MFA, device authentication, and clearly scoped permissions.
- Comprehensive Logging – Connection history, chat transcripts, and file-transfer records support audits and root-cause analysis.
The productivity multiplier appears when each of those features works seamlessly together; otherwise, technicians waste precious cycles logging into separate portals or coaching users through convoluted set-up steps.
Splashtop SOS
Overview – Splashtop targets SMBs and education with mix-and-match licensing: pay per technician rather than per endpoint. Users launch a nine-digit code from sos.splashtop.com; no install is required for one-time assistance.
Mark is an ideal spot to point readers toward a resource that summarises many of these capabilities. Teams evaluating the best remote support software solutions will find a concise feature matrix, transparent pricing tiers, and industry-specific case studies-useful benchmarks when building an internal business case.
Productivity Highlights
- 4:4:4 color streaming at up to 60 fps-useful for creative suites.
- Group-based permission profiles map to LDAP or Azure AD.
- On-prem gateway option helps meet data-sovereignty requirements in finance and healthcare.
Drawbacks
- Advanced AR camera share incurs an extra fee.
- The marketplace of third-party integrations is smaller than TeamViewer’s.
TeamViewer
Overview – TeamViewer has dominated the remote-access space for over a decade. Its QuickSupport executable launches without full installation, perfect for helping a one-off customer. Business and Premium plans enable unattended access, allow group management of thousands of devices, and support wake-on-LAN for powered-down endpoints.
Productivity Highlights
- Multi-user sessions let a senior engineer observe a junior technician’s work in real time.
- Conditional access integrates with Azure AD, so only approved identities can initiate high-privilege connections.
- Augmented-reality add-on uses a smartphone camera so field engineers can “see” hardware racks or factory kit as if standing onsite.
Drawbacks
- The pricing can escalate quickly for large concurrent volumes.
- Some admins report false “commercial use” suspensions on personal devices, requiring manual reinstatement.
AnyDesk
Overview – At under 4 MB, AnyDesk’s installer is lighter than many PDF manuals. Its proprietary DeskRT codec transmits only the pixel deltas between frames, producing remarkably smooth motion on limited bandwidth.
Productivity Highlights
- Portable version runs from a USB stick-handy when admin privileges are unavailable.
- Session recording helps trainers review troubleshooting steps or satisfy compliance audits.
- TCP tunnelling lets you forward testing ports without opening extra firewall rules.
Drawbacks
- Advanced identity integrations (Okta, SSO) sit behind higher-tier plans.
- Fewer marketplace plug-ins than TeamViewer or Zoho Assist.
Zoho Assist
Overview – Built for help-desks, Zoho Assist bakes in screen-sharing, unattended access, and custom branding. Deep ties to the Zoho SaaS ecosystem entice companies already running Zoho Desk or Zoho CRM.
Productivity Highlights
- Bulk deployment wizard pushes unattended agents across Active Directory or via an MSI.
- Reboot and reconnect streamlines patches that require a restart-technicians hop back into the session automatically.
- Web-based console means no desktop app is mandatory.
Drawbacks
- 3D-graphics performance lags behind AnyDesk.
- Reviewers on Capterra mention that multi-monitor navigation can feel fiddly when working on four-screen trading floors.
Choosing the Right Software for Your Team
Before drawing up a purchase order, map your environment against four decision pillars:
- Support Model – Internal IT, MSP, or customer help-desk? MSPs may favor concurrent-technician licensing, whereas in-house departments lean toward device-based metrics.
- Compliance Needs – Healthcare entities require HIPAA BAAs; finance firms need PCI logs; EU operations might demand GDPR data-processing agreements.
- Device Diversity – A Windows-only shop might exploit RDP Gateway, but mixed OS fleets need broader protocol coverage.
- Budget vs. Scale – Chrome Remote Desktop costs zero, but lacks enterprise logging; TeamViewer Tensor offers deep analytics but commands a premium.
A Forrester study found that organizations that piloted at least two platforms achieved a 19% better first-call resolution rate after rolling out their final choice, compared with teams who skipped hands-on trials.
Best Practices to Maximize Productivity
- Train technicians on hotkeys, permission toggles, and secure file-transfer paths- shortcuts slash session length by 15 % on average.
- Segment roles so contractors cannot pivot between customer environments.
- Monitor session metrics MTTR, session count, and peak concurrency to justify staffing and licensing renewals.
- Patch endpoints frequently; an unpatched remote agent is a liability hackers can exploit, as the Cybersecurity & Infrastructure Security Agency warns in multiple advisories.
Conclusion
Robust remote-support software no longer sits in the “nice-to-have” column-it’s fundamental infrastructure for hybrid organizations and globally distributed customers. Tools that blend iron-clad security, snappy performance, and smart automation empower technicians to troubleshoot faster, users to remain productive, and businesses to reach new markets without adding headcount.
Frequently Asked Questions
How do remote-support tools keep customer data private?
Leading vendors encrypt every pixel with AES-256, enforce multi-factor authentication, and store audit logs in ISO 27001-certified clouds. Admins can also disable clipboard sync or file transfer to prevent accidental data leakage.
Can remote-support software handle mobile devices?
Yes. Products such as Splashtop SOS and TeamViewer Mobile Control let technicians view or control Android and iOS screens, push configurations, and even capture crash logs – essential for supporting BYOD field workers.
Which metrics prove that a tool boosts productivity?
Track mean time to resolution (MTTR), first-call resolution rate, ticket volume per technician, and user satisfaction (CSAT). Tools that automate session reporting provide this data out of the box, letting managers fine-tune staffing levels and training programs.
Are you frustrated with losing money through hidden fees during international money transfers?
Anyone who has sent money abroad understands the annoyance of receiving a smaller amount than expected. Billions of dollars disappear each year due to hidden fees which create huge issues in international money transfers.
But here’s the good news…
Armed with proper information and a strategic plan you can sidestep these hidden transfer fees.
Transfer fees that aren’t obvious will reduce the amount your family and business associates receive when sending money from the USA to the Philippines. Learning about fee structures marks the first move toward mastering the transfer system.
The Inside Scoop:
- Understanding the Hidden Fee Problem
- The Most Common Fee Traps to Watch For
- How to Compare Transfer Services Like a Pro
- Smart Strategies to Slash Hidden Costs
- Best Practices for USA to Philippines Transfers
Understanding the Hidden Fee Problem
Hidden fees in international transfers refer to undisclosed charges that appear when you start a transaction.
Here’s why they’re so sneaky:
Providers advertising “zero fees” or “fee-free transfers” earn their money through poor exchange rates.
Recent statistics show that hidden exchange rate markups constitute 32% of cross-border payment fees totaling $5.8 billion which impact both individual and business transactions.
Billions of dollars disappear through fees that customers aren’t properly informed about.
When you send money to The Philippines or any other country, these hidden charges can include:
- Currency conversion markups (2-5% above mid-market rates)
- Receiving bank fees
- Intermediary bank charges
- Weekend or after-hours surcharges
Cross-border transactions incur traditional bank and payment processor fees that reach $50 per transaction and more before accounting for extra indirect costs like poor exchange rates.
The Most Common Fee Traps to Watch For
Where do these hidden fees remain unnoticed?
Exchange rate markup stands as the primary hidden cost factor in money transfers. A provider charges you an inferior exchange rate to the market rate to capture the difference as profit.
If your provider offers a USD to PHP rate of 54.00 instead of the market rate of 56.00 you are paying a hidden fee of 3.6% which results in your recipient receiving $36 less on a $1,000 transfer.
Other common fee traps include:
- Intermediary bank fees: When your money passes through multiple banks, each one can take a cut
- Receiving fees: Some banks charge the recipient for accepting international transfers
- Processing speed fees: Paying extra for “instant” transfers that could be standard
- Payment method fees: Being charged extra for using a credit card instead of a bank account
Global companies send $23.5 trillion annually across borders and pay at least $120 billion in charges due to hidden fees and exchange rate surcharges.
How to Compare Transfer Services Like a Pro
To secure the best deal requires examining additional costs beyond the advertised rate. Here’s how to compare services effectively:
1. Calculate the TOTAL cost
Don’t just look at the transfer fee. Calculate:
- The transfer fee
- Assess the markup on exchange rates by comparing it to Google’s rate.
- Any receiving fees
2. Check the ACTUAL amount received
The key figure you need to know is how much money will be delivered to the recipient in Philippine Pesos. Before you proceed with the transfer request you must obtain this precise amount.
3. Compare multiple providers
Check at least 3-4 different services including:
- Banks
- Online transfer services
- Money transfer operators
- Payment apps
Traditional bank transfers typically incur higher costs and take longer to complete than fintech or blockchain-based payment solutions.
Smart Strategies to Slash Hidden Costs
Ready to stop paying unnecessary fees? My preferred tactics for reducing international money transfer costs are outlined below:
Send larger amounts less frequently
Multiple fees per transaction means that sending $1,000 at once is more cost-effective than sending $250 four times. Consolidate your transfers when possible.
Choose the right payment method
Using bank transfers or debit cards tends to result in lower fees than those incurred through credit card payments. Certain service providers impose additional charges for their “instant” transfer options.
Plan ahead for better rates
Services provide better rates for money transfers when you can wait 2-3 business days instead of requiring instant delivery.
Consider alternative providers
Using alternative payment providers can help businesses avoid or reduce hidden costs by offering lower fees and clear exchange rates.
International transfers of $100,000 can result in thousands of dollars in losses because of undisclosed fees and currency rate markups which vary between 1.5% and 7.5% based on the provider.
Best Practices for USA to Philippines Transfers
The Philippines stands as one of the top remittance destinations globally because millions of Filipino workers overseas send funds back to their home country. The following specific tips will help you when you transfer money from the USA to the Philippines.
1. Compare specialized services
Certain transfer services that specialize in the USA to Philippines corridor deliver better rates than general providers. Identify services that maintain strong operations in both the USA and the Philippines.
2. Watch for peso pickup options
Cash pickup is the preferred transaction method for many money recipients in the Philippines. It’s important to select a pickup network offered by providers that matches your recipient’s convenience requirements because each provider offers different pickup networks.
3. Check for recipient fees
A selection of Philippine banks impose fees when receiving international money transfers. You should ask your recipient to verify whether their bank imposes fees for receiving wire transfers.
4. Be aware of timing differences
The Philippines operates on a time zone that places it 12-15 hours ahead of the USA depending on your specific time zone. International money transfers started in the USA at the end of the day will usually be processed in the Philippines during the next business day.
The cost of international wire transfers may rise due to hidden fees including intermediary bank charges and incoming wire fees paired with currency markups. Banks often increase transfer costs by applying markups between 2% and 5% above the mid-market exchange rate.
Quick Answers About International Transfers
“How long does a transfer take?” Traditional banks: 3-5 business days. Specialized services: minutes to hours.
“Is it safer to use a bank?” Not necessarily. Licensed money transfer companies maintain the same security protocols as banks yet they tend to provide better rates.
“What documents do I need?” You must provide valid identification as well as proof of funds for substantial transfers. Recipients typically need ID to collect.
Final Thoughts on Beating Hidden Fees
People across the globe lose billions in hidden fees during international money transfers but it’s possible to avoid this financial loss. If you learn to spot hidden fees and evaluate services meticulously you’ll be able to save a substantial amount of money.
Remember these key points:
- Exchange rate markups are the biggest hidden fee – always compare the rate to the real mid-market rate
- Total cost matters more than advertised fees – calculate everything
- Alternative providers often beat traditional banks for international transfers
- Specialized services can offer better deals for specific country corridors like USA to Philippines
Before you execute your next transfer analyze a minimum of three money transfer services to make an informed decision. The annual savings can reach several hundred dollars which should go to your family in the Philippines instead of increasing financial institution profits.
In times of sharp and unpredictable price swings, traders need tools that enable fast data analysis and decision-making. Live (real-time) charts have become an integral part of the trading process. They allow you to not only monitor the price but also see the behavior of the market – taking into account volume, volatility, liquidity, and technical patterns.
In this article, we will look at how live charts help traders reduce risks and what strategies are used in different market segments, including forex, commodities, and cryptocurrency.
Why Live Charts Are Critical During High Volatility
High volatility is not just about large price swings. It is about conditions that increase the risk of significant losses in a short periods. CME Group statistics show that during periods of macroeconomic data releases (such as CPI or Fed decisions), volatility in major assets increases by an average of 35-50% compared to normal levels.
Live charts help in such conditions:
- Monitor market reactions in real-time (e.g. to interest rate releases)
- Assess liquidity using order book and trading volumes
- Identify spikes and corrections – and react quickly
Key Features of Live Charts for Risk Management
Using Volatility Indicators
Indicators like Average True Range (ATR), Chaikin Volatility, or Bollinger Bands can measure market “tension”. When the price range widens, a trader can reduce the position size or move the stop loss further to avoid being knocked out by the swings.
Pattern and Level Recognition
Live charts show technical analysis figures: triangles, flags, and double tops. This helps to make decisions based not on emotions, but according to the market structure.
Real-Time Information Update
There is no delay between price and reaction – unlike static daily or weekly charts.
Current Session Context
The live chart shows the price, trading volumes, clusters, and dominant direction. This is especially vital for intraday trading.
Practical Application Examples: Gold and Cryptocurrency
Let’s consider the behavior of a trader who works with gold (XAU/USD). Let’s say he analyzes the chart on a platform and notices an increase in volatility. Bollinger Bands are expanding the price beyond the channel boundaries – this may be a signal of trend continuation.
Trader:
- Sets a floating stop loss based on ATR.
- Reduces the position size by 2 times when important news is released.
- Switches to a 15-minute chart to track the reversal.
In the case of cryptocurrency (for example, BTC/USD), where spreads and liquidity are less stable, the trader additionally uses cross-analysis — comparing the charts of Bitcoin and Ethereum to confirm the signal. Volume indicators (OBV, VWAP) are also actively used to avoid false breakouts.
Advanced Risk Management with Live Charts
Traders use combinations of methods:
- Dynamic stop losses — adjusted manually or by the indicator when the trend moves.
- Take profits with partial fixation — profit fixation in stages (for example, 30%, 50%, 100%) when the targets are reached.
- Risk-to-reward ratios (R: R) — only transactions with a ratio of 1:2 and higher are accepted.
- Taking into account the macro background — for example, before the FOMC meeting, the trader switches to cash and watches the market without open positions.
Using Charts on Different Time Frames
Working with multiple timeframes allows you to see the “big picture”:
- 1D / 4H – help to establish key resistance and support levels.
- 1H / 15M – give signals to enter a trade.
- 1M / tick – used by scalpers and HFT.
Comparative analysis of charts on different timeframes reduces the probability of an entry error. If the signal is confirmed on two or more scales, the probability of success is higher.
Peculiarities of Risk Management in Different Markets
Current Sources and Analytics
According to the Deloitte Report: The Future of Capital Markets 2024, more than 70% of professional traders use algorithms that work on graphic patterns. That is, even automated systems are built around live charts.
An analysis of CME Group reports shows that traders who use a combination of graphical analysis and futures hedging reduce drawdowns by an average of 1.6 times compared to participants who work “on the news.”
Errors when Working with Charts
Despite their effectiveness, live charts do not guarantee success. Common mistakes:
- Overcomplicating the analysis: too many indicators.
- Emotional trades based on candlesticks without confirmation.
- Ignoring fundamental factors (e.g. corporate reports or macro data).
How Live Charts Help Traders Be Proactive
One of the most crucial advantages of live charts is the ability to react and anticipate market behavior. This becomes especially pivotal on days when key macroeconomic indicators are published, such as Non-Farm Payrolls, the Consumer Price Index (CPI), or the US unemployment rate.
Experienced traders use price clusters, tick charts, and correlations between assets. For example, the correlation between the dollar index (DXY) and gold (XAU/USD) allows you to make decisions on one position based on the dynamics of the other. It is not a theory – according to MacroMicro, the correlation between DXY and XAU/USD at the beginning of 2025 remains consistently negative at -0.85.
Many also use Volume Profiles to assess where the key interests of market participants are concentrated. Areas with the highest volumes often act as reference levels for price movement.
Using Live Charts in Algorithmic Trading
Live charts also play an important role in automated systems. Algorithms, including those used by hedge funds, integrate Japanese candlestick, EMA cross, and Fibonacci analysis into their trading logic.
Example: a trading bot running on Python with TA-Lib and ccxt libraries can automatically:
- Detect breakout signals on Bollinger Bands;
- Rebuild stop losses when average volatility changes over the last 30 minutes;
- Close positions if RSI on the chart goes beyond threshold values.
It clearly proves that live charts are not just visualization but the basis of quantitative trading.
Recommendations for Beginner Traders
- Don’t overload the chart: maximum 2–3 indicators at a time.
- Learn from history: look at how the market behaved in similar situations in the past.
- Use alert notifications: no need to look at the screen 24/7 — modern platforms allow you to set signals.
- Analyze mistakes: write down why you opened a trade and how it ended.
- Separate strategy and psychology: even the best signals won’t help if the trader gives in to emotions.
Final Thoughts
Live charts are the primary interface between a trader and the market. In an environment where every second counts, they allow you to control risks, identify opportunities, and act with intelligence.
Since 2024, Refinitiv has reported a growing adoption of real-time data not only by institutions but also by individual investors. More traders now recognize that building a sustainable strategy—especially in volatile markets—is nearly impossible without access to live charts.
It is also worth noting that many professional traders in 2025 are actively using multi-platform solutions that integrate live charts with trading terminals, news analysis systems, and even AI modules. This approach allows you to receive signals from different sources, including social networks and economic news feeds, and instantly apply them in practice. The higher the information density, the more important the visual organization of data is – this is what live charts do, turning chaos into a readable picture of market behavior. As a result, the trader not only reduces risks but also gains a strategic advantage over those who work on “dumb” platforms without visual cues and indicators.
Link to live chart XAU/USD: https://primexbt.com/price-chart/currencies/xau-usd
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