KredosAi vs. Solutions by Text: AI-Driven Collections Optimization (2026)

KredosAi was founded in 2021 by Balaji Sridharan and Dave Thoms, both former T-Mobile executives who built the company after experiencing the delinquency problem from inside a Tier 1 operator. It uses a Multi-Armed Bandit machine learning algorithm customized for collections to optimize digital engagement across telecom, auto lending, and financial services.

Solutions by Text (SBT) was founded in 2008 by Danny Cantrell in Dallas; it has spent 17 years building the compliance infrastructure that consumer finance companies need to communicate with borrowers over text. Its FinText platform handles SMS, MMS, and RCS messaging with TCPA/FDCPA compliance and embedded payments. CEO David Baxter joined in 2021.

KredosAi and Solutions by Text serve distinct purposes. KredosAi uses behavioral AI to determine the optimal message, channel, and timing for each account based on outcomes data. Solutions by Text ensures compliant delivery of messages with embedded payments. This comparison focuses on how each platform addresses its primary function.

Quick Comparison: KredosAi vs. Solutions by Text

AI Methodology: Decision-Making Approaches Compared

Most RFP processes treat these two platforms as direct competitors, but they solve different problems. This difference shapes how they should be evaluated.

KredosAi: MAB Reinforcement Learning

For each delinquent account, the KredosAi engine makes three decisions:

1. Chooses the message variant, channel (SMS, RCS, email), and send time most likely to cure the account.

2. Updates continuously based on actual resolution outcomes, not the predictions made at setup.

3. Deploys Agentic AI capabilities including voice agents as the multi-agent framework approaches release.

TCPA/FDCPA guardrails and human-in-the-loop review sit in the messaging layer. KredosAi is also a FICO Platform partner, integrating collections optimization into the stack many banks already use for credit decisions.

Solutions by Text: Compliance-First Infrastructure

SBT's FinText platform answers a different question: not which message, but will this message go out correctly?

1. Sends compliant SMS, MMS, and RCS at scale with TCPA/FDCPA/CFPB guardrails built into the architecture.

2. Embeds payments directly in the thread: Apple Pay, Google Pay, TextPay, and Triple Play Pay.

3. Manages opt-in/opt-out via Stop Safety Net, honoring revocations across all channels and carriers.

SBT actively maintains carrier compliance with T-Mobile, Verizon, and AT&T policies separately from federal regulatory compliance.

What SBT doesn't do: determine which content, timing, or channel drives the best financial outcome at the account level. The platform delivers messages compliantly. It does not learn from what resolved the debt.

Side by side: what each platform decides

Any vendor can send a compliant text, but optimizing delivery across millions of accounts in real time is a separate challenge. SBT provides infrastructure, while KredosAi delivers optimization.

ROI and Documented Outcomes

KredosAi: 20x+ ROI at Fortune 50 Scale

KredosAi reports 20x+ ROI across Fortune 50 deployments:

• 11.5% reduction in write-off rates

• 13.6% increase in customer lifetime value

• $50M+ annual bottom-line benefit for some Fortune 50 clients

• +16% cure rate improvement (internal source only)

• 7.4% suspend reduction (internal source only)

Procurement can be validated before commitment.

Solutions by Text: Up to 400% ROI Claimed

SBT's headline claims (SBT website; baseline not specified):

• Up to 400% ROI

• 97% reduction in time to revenue

Published commercial data behind those claims:

• 60% YoY revenue growth in 2024 (PRNewswire, January 2025)

• Nearly 2 billion messages delivered in 2024

• Inc. 5000 No. 1,703 in 2025; 257% three-year growth

Vertical Fit

KredosAi and SBT overlap directly in auto finance and financial services. Telecom is KredosAi territory; SBT has no stated telco use cases. That makes the overlap narrower than the overall comparison.

Auto Finance

Auto lending is where these two platforms land on the same prospect's shortlist most often, and where the buy decision gets most complicated. Subprime delinquencies are at their highest since the 1990s. Lenders are looking at the same tradeoff telcos face: recovery cost vs. long-term customer value. That's precisely what KredosAi's MAB engine is designed to optimize.

SBT's auto finance track record is longer. SAFCO is a named case study. FinText covers the full auto loan lifecycle from origination through collections. The January 2026 acquisition of Triple Play Pay expanded embedded payment options for lenders who need flexibility across payment methods. 

Auto lenders must decide whether they need compliance-focused infrastructure to ensure proper outreach or an optimization engine that determines the most effective engagement for each account. Some lenders integrate both solutions.

Financial Services

KredosAi integrates with the FICO CCS Platform and counts Anderson Brothers Bank as a named FS client. SBT's Glia partnership brings FinText into the Glia Unified Interaction Platform used by 500+ banks, credit unions, and insurance companies. SBT reports 800+ FS customers. Neither vendor has named Fortune-level FS clients publicly, which is a gap worth probing in both evaluations.

Compliance and Security

Both platforms are built for regulated consumer finance environments. The architectural difference is where compliance sits relative to the optimization logic, and that difference drives the rest of the evaluation.

KredosAi built TCPA/FDCPA guardrails into its AI optimization engine, with human-in-the-loop review in the messaging layer. SOC 2 Type 2 certification runs on enterprise AWS.

SBT built compliance as the product's foundation, separate from any optimization layer.

Integration

Pricing

Neither vendor publishes a rate card, so pricing must be evaluated through process and scope discussions.

Vendor Background

Seventeen years vs. five. $145M raised vs. just over $10M. 1,500 customers vs. Fortune 50 enterprises. These numbers describe genuinely different companies at genuinely different stages, and both are relevant to a multi-year platform commitment. That context matters before you compare fit.

SBT is a profitable, scaling business with institutional backing and a wide installed base in consumer finance. KredosAi is a focused early-stage company whose commercial model, the no-cost pilot, reflects a team confident enough in measurable outcomes to let data make the case rather than a sales motion. Revenue has grown 6x over two years. The Series A was oversubscribed. BMW i Ventures' thesis covers physical AI, agentic AI, and AI-native enterprise software. Their investment in KredosAi reflects a view that existing tools structurally underserve the delinquency optimization problem.

When to Consider Each Platform

Buyers should recognize that KredosAi and Solutions by Text address different organizational needs. Clarifying whether your primary challenge is optimization or compliance will make the evaluation process more straightforward.

If the question is: which message drives cure for each account?

KredosAi. The MAB engine runs continuous experiments across your portfolio, learns from actual resolution outcomes, and reallocates in real time. It gets smarter. A static sequence, however well designed, does not. If cure rate and write-off reduction are the primary KPIs, and you need a platform that keeps learning rather than executing a fixed playbook, KredosAi is purpose-built for that.

If the question is: can we send compliant, payment-enabled text messages at scale?

In practice, some auto lenders deploy SBT for compliant, payment-enabled delivery and KredosAi for determining optimal outreach. The platforms can be complementary, and using both may address broader operational requirements.

Choose KredosAi if:

• Cure rate and write-off reduction are your primary KPIs

• You need real-time, per-account optimization

• SOC 2 Type 2 and TCPA/FDCPA guardrails are required

• You're considering build vs. buy and need data to decide

• Agentic AI and voice features are important

• FICO Platform integration is a priority

Choose Solutions by Text if:

• Layered compliance infrastructure is your primary goal

• Embedded payments are required

• Consumer finance, BNPL, or ARM is your main vertical

• RCS with a named financial services deployment is needed now

Frequently Asked Questions

What is the difference between KredosAi and Solutions by Text?

KredosAi leverages a Multi-Armed Bandit algorithm to optimize message, channel, and timing per account using outcome-based learning. Solutions by Text offers a compliance-first messaging platform with embedded payments tailored for consumer finance. KredosAi focuses on optimization, while Solutions by Text ensures compliant delivery.

Is Solutions by Text a competitor to KredosAi in telecom?

No. Telecom is not a stated vertical for Solutions by Text. Its markets are consumer finance, auto lending, and ARM. KredosAi competes with SBT in auto finance and financial services, not in enterprise telecom.

Should we build an in-house collections messaging platform instead?

In-house builds come up in most enterprise RFPs. The appeal is real: model control, no licensing cost, proprietary data integration. What gets underestimated is the annual cost of ML engineering talent, compliant multi-channel messaging infrastructure, MAB optimization, and ongoing model maintenance. That typically exceeds the combined cost of a purpose-built optimization engine and a compliance messaging platform.

That gap, ongoing team cost and legal exposure against a low infrastructure baseline, is what the build vs. buy math tends to miss.

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