Yes. TAZI connects via REST / event APIs and we support common Core platforms, CRM’s such as Salesforce, marketing automaton systems such as HubSpot, and data warehouses such as Snowflake. We aim to simply add AI intelligence to your existing workflows.

Over the years we’ve seen less and less data required to get the initial value. Oftentimes, no one is sure if there is enough data, so this is why we built the TAZI Data Profiler that conversts raw data into AI-ready data and flags any gaps, taking out the guesswork. 

On top of that, our continuous learning and adaptive technology enables TAZI Solutions to learn and improve results as new data becomes available, so it’s best to just start and the value typically grows from there.

And, we have trusted data partners that can provide the member / client behavior and life events data to further reduce data requirements for financial institutions.

Perfect data is a myth. No one has perfect data and that’s not a realistic goal. Business, market, and clients change all the time and so does data collection. 

Most successful organizations start with what they have and build from there. Otherwise, you may never start and those that do may get too far ahead to catch.

The real question is how to release your data to help you grow the business. We’ve seen our customers do this time and time again, so we can’t emphasize enough to just start, small, somewhere, but start.

Yes. This is one of our ready-to-go Growth solutions that constantly analyzes client / member data from CRM, engagement platforms, financial platforms to find patterns that lead to attrition. 

Your teams will get lists of clients / members predicted to churn along with how to engage with them (time, channel, message). Our customers that are using this solution have seen as much as 15% increase in retention, and also more growth from deepening relationships that resulted from their retention outreach efforts.

Yes. This is one of our ready-to-go Growth solutions that first looks at your clients / members to predict the Ideal Client Profile, and then we partner with data providers that have a broad view into business’ and people’s financial situations to identify best targets.

We’ve found that Ideal Client Profile patterns change more often than anticipated, so being able to stay agile and continue to acquire ideal clients, as their profiles change, results in more profitable growth.

Yes. This is one of our ready-to-go Growth solutions that utilizes CRM, transactional data, and 3rd party data to predict member / client behavior and life events and recommends messaging for client outreach, at scale: campaigns, service, or sales outreach programs. 

TAZI also integrates with marketing automation tools such as HubSpot, or CRM such as Salesforce to make it easy to deploy the messaging at scale.

Yes. This is one of our ready-to-go Growth solutions that predicts clients / members that are loyal, based on their behavior and decisions, to help credit unions and banks identify new members / clients that fit credit union’s/bank’s ideal client profile to help them grow more sustainably and profitably, rather than just grow in member / client numbers.

Yes. This is one of our ready-to-go Growth solutions that looks at member / client communications across any channel, internal and public. It predicts sentiment, topics, and complaints, and it provides recommendations for actions for different teams: marketing, product, sales. Our unique approach is that we are not limited to any specific data source and new data can be added at any time. 

Most credit unions and banks don’t have the data from all communication channels available from the start, but as you enable the data, you can just add it to the TAZI Growth Solution and see the results. 

Yes. Traditionally, NPS scores have been based on a once/year survey which catches members / clients in one moment and while valuable, the responses may not be fully indicative of the overall sentiment, throughout the year, that may lead members / clients to leave and not recommend their credit union or bank. 

This is why we believe that by having real-time access to member / client sentiment, and most important topics (positive and negative), throughout the year, you can get additional insights and be more proactive in addressing issues to increase member / client satisfaction.

Yes. With TAZI’s hyper-personalization solution, credit unions and banks can be more relevant to each member / client, which is especially expected by younger generations. 

Yes. This is one of our ready-to-go Growth solutions that  helps marketing teams in credit unions and banks predict which channels are best for each campaign to increase engagement and conversion rates.

Testing our ready-to-go Growth solutions takes only up to 2 weeks. Full deployment in production is 4–6 weeks, and our customers typically see business impact in the first quarter following the implementation.

Yes. This is one of our unique capabilities. We are an AI Platform with multiple Solutions that drive growth. So, you would start with one solution and deploy additional solutions once you have the comfort and confidence in the platform and process. 

We see AI as a journey and one that you want to take at your pace. Our goal is to partner for the entirety of that journey, so we keep growing the library of Growth solutions we offer.

We are obsessed with bringing you the ROI and value. We meet quarterly to review results to “keep all of us honest”. 

We also want to make sure that we keep your costs down, so in addition to assigning a customer success manager and product support, we also assign a senior data scientist to look over all your AI solutions. This way you don’t have to hire more technical experts and incur additional costs from implementing AI.

Yes, TAZI has been helping financial institutions scale AI securely and in compliance, since 2017. Our mission is to democratize AI across the organization by enabling business teams directly, not requiring deep technical expertise to implement and manage AI solutions. 

Most of our customers start with 1-2 solutions and scale from there. This way they can scale AI at their own pace, knowing it’s always done securely. 

Transparent and explainable AI, plus Human-In-The- Loop mechanisms, are patented parts of our platform and have always been at the core of our approach, which is absolutely essential for a regulated industry such as financial services. We would not recommend implementing any AI solution that doesn’t meet these principles.

Every prediction is paired with human-readable explanations, audit trails, and bias checks to satisfy regulators and internal risk teams. 

At this time, we are not fine tuning an LLM model itself. While we have done this in the past, we have found that if the problem is broken down into smaller parts, then good prompting is a better approach, and not as expensive as training an LLM model. 

Of course, if we see that over time prompting is not producing good results then we would fine tune the LLM itself.

You can choose which LLM you want to use and you can use multiple LLMs. This is configured in TAZI, so only LLMs that have been configured can be used for any TAZI solution. 

In terms of LLMs, most of our customers use local LLMs deployed locally, or in their private cloud. Some are starting to use Azure LLM. If you are already using Azure LLM and it has been approved, you can use it in TAZI too, otherwise we would advise to use a local LLM. 

We utilize the following steps and methods: 

1. Advanced Prompt Engineering: We employ techniques such as: 
1. Clear and Specific Instructions
2.  Contextual Grounding (RAG)
3. Few-Shot Prompting
4. Chain-of-Thought Prompting
5.  Repetition of Key Instruction, Role-Playing:
2. Model Configuration: temperature control, selection of different LLMs. 
3. Post-Processing and Guardrails:
1. Utilizing multiple LLMs to supervise the outputs or check for inconsistencies in the outputs. 
2. Human validation, evaluation and testing results via dashboards. 

Advanced Prompt Engineering and  Post-Processing & Guardrails are used to assess and eliminate bias, just like they are used mitigating hallucinations.

We do not train LLMs, when there is enough high quality domain specific data and necessary hardware, we could fine-tune models..

TAZI’s variety of real-time ML methods (classification, anomaly detection, clustering, data analysis) and interactive dashboards and interactive explanations allow users to check bias in the outputs..