Salt Technologies AI AI
Starting at $15,000

AI Integration Sprint

Add AI features to your existing product. No rewrite needed. Shipped in 4 weeks.

14+

Years of Experience

800+

Projects Delivered

100+

Engineers

4.9★

Clutch Rating

You do not need to rebuild your product to add AI capabilities. The AI Integration Sprint adds intelligent features to your existing codebase: smarter search, content generation, document processing, predictive analytics, and more. We work in your repository, follow your coding standards, and submit production-ready code with tests and documentation. Your tech stack stays the same. We adapt to it.

Why Most AI Integration Projects Fail

Adding AI to an existing product seems straightforward. In practice, most teams underestimate the complexity and end up wasting months and budget on approaches that do not work.

The "rip and replace" trap

Teams assume they need to rebuild their product architecture to add AI. They start a 6-month rewrite, burn through budget, and ship nothing. Your existing architecture can support AI features with the right integration approach. A rewrite is almost never necessary.

AI features that work in demos but fail in production

A Jupyter notebook proof of concept is not production code. Without proper error handling, rate limit management, latency optimization, and fallback logic, AI features break under real load. Your users see timeouts, hallucinated responses, or blank screens.

Solo freelancers who cannot navigate your codebase

You hire an "AI expert" who knows Python and LLM APIs but cannot work in your React/Node.js monorepo, does not understand your data model, and delivers a standalone script instead of integrated code. Now your team has to redo the integration themselves.

Vendor lock-in from AI platform add-ons

AI features bolted on via third-party platforms (Salesforce Einstein, HubSpot AI, etc.) give you limited customization, unpredictable pricing as usage grows, and zero portability. When your needs outgrow the platform, you start from scratch.

The cost of getting it wrong: A failed AI integration project wastes $30,000 to $100,000 in engineering time and opportunity cost. Worse, it creates internal skepticism about AI that delays adoption by 6 to 12 months while competitors ship AI-powered features.

The solution: A structured 4-week sprint with a full-stack AI team that works in your codebase, follows your coding standards, and ships production-ready AI features with tests, documentation, error handling, and monitoring. Fixed scope, fixed price, no surprises.

What Is an AI Integration Sprint?

An AI Integration Sprint is a fixed-scope, 4-week engagement where a dedicated AI engineering team adds intelligent features to your existing product or platform. Unlike a ground-up rebuild, the sprint works within your current architecture, your repository, and your tech stack. The result is production-ready AI capabilities shipped as reviewed, tested, and documented pull requests.

At Salt Technologies AI, our integration sprints combine large language models (OpenAI GPT-4o, Anthropic Claude, Google Gemini) with custom prompt engineering, evaluation frameworks, and production-grade infrastructure. We handle the full integration lifecycle: codebase review, API design, data pipeline construction, prompt optimization, error handling, performance testing, and deployment. Your team reviews every PR and owns all code from day one.

Common AI features we integrate include semantic search, content generation, document processing, predictive analytics, natural language interfaces, and intelligent classification. Each feature is designed to work with your existing data, your existing user experience, and your existing deployment pipeline. No new infrastructure to manage, no separate AI service to maintain.

4 Weeks

From Kickoff to Production

1-3 Features

Shipped Per Sprint

Zero Rewrites

Works With Your Stack

The Business Impact of Adding AI to Your Product

AI features are no longer a "nice to have." They are a competitive differentiator. Here is what businesses see after integrating AI into their existing products.

Increased User Engagement

Products with AI-powered search, recommendations, and content generation see 20-40% increases in user engagement and time-on-platform.

20-40%

More engagement

2-3x

Feature adoption

Reduced Manual Work

AI-powered document processing, classification, and data extraction eliminate hours of repetitive manual work, freeing your team to focus on high-value tasks.

60-80%

Less manual processing

5-10x

Faster data extraction

Revenue Uplift

AI-powered recommendations, personalization, and smart search directly increase conversion rates and average order values. SaaS products with AI features command higher pricing tiers.

10-25%

Conversion lift

15-30%

Higher ARPU

Competitive Advantage

In 2026, users expect AI-powered features. Products without smart search, content generation, or predictive analytics are losing deals to competitors who have them.

73%

Of buyers prefer AI features

4 Weeks

To close the gap

Metrics based on industry benchmarks and client engagement data. Actual results depend on product type, user base, and implementation scope.

Discuss Your AI Integration Goals

We will identify the highest-impact AI features for your product on the discovery call.

Is AI Integration Right for You?

The AI Integration Sprint is designed for product teams that have a working product and want to add AI capabilities without disrupting what already works.

  • You have an existing product or platform and want to add AI features
  • You do not want to rebuild your application from scratch
  • You need AI features that work with your existing data and workflows
  • You want it shipped fast, by a team that has done it before

If two or more sound like you, let's talk.

Book a Free Discovery Call

AI Integration Use Cases

These are the AI features we most commonly integrate into existing products. Each one is designed to layer into your current architecture without a rewrite.

1

AI-Powered Semantic Search

Replace keyword search with AI-powered semantic search that understands meaning, not just exact matches. Users find what they need even when they do not know the exact terminology.

2

Content Generation and Summarization

Integrate AI writing, summarization, or translation features directly into your platform. Let users generate drafts, summaries, or translations from within your product.

3

Document Processing and Data Extraction

Automate extraction of structured data from uploaded documents: invoices, contracts, forms, and reports. Eliminate manual data entry with AI that reads and classifies documents.

4

Predictive Analytics and Recommendations

Add forecasting, anomaly detection, or recommendation engines to your existing analytics dashboards. Turn historical data into actionable predictions your users can act on.

5

Natural Language Interfaces

Add natural language query capabilities to dashboards, admin panels, or data tools. Let users ask questions like "Show me last month revenue by region" and get instant results from your database.

6

Intelligent Classification and Routing

Automatically categorize, tag, and route incoming content: support tickets, form submissions, emails, or user-generated content. Reduce manual triage time by 80% or more with AI that learns your taxonomy.

What's Included in Your AI Integration Sprint

Eight deliverables. Production-ready from day one. Everything you need to ship AI features that work in your existing product.

1

AI Features Integrated Into Your Codebase

Production-ready AI capabilities added directly to your existing repository. Submitted as reviewed pull requests that follow your coding standards, pass your CI/CD pipeline, and are ready to merge.

Your repo, your standards PR-based delivery CI/CD compatible
2

API Endpoints for AI Capabilities

Clean, documented REST or GraphQL endpoints that expose AI features to your frontend, mobile app, or third-party integrations. Designed with rate limiting, authentication, and versioning from the start.

REST / GraphQL Rate limited Versioned
3

Data Pipeline for AI Model Inputs

Automated pipeline that prepares your existing data for AI consumption. Handles data extraction, transformation, embedding generation, and indexing so AI features always work with fresh, accurate data.

ETL pipeline Auto-sync Embedding generation
4

Prompt Engineering and Evaluation Suite

Optimized prompts with systematic evaluation: test datasets, accuracy benchmarks, regression tests, and a framework for your team to iterate on prompts after handoff. No guesswork, just measured, repeatable AI quality.

Prompt optimization Test datasets Regression testing
5

Error Handling and Fallback Logic

Production-grade error handling for every failure mode: API timeouts, rate limits, model unavailability, malformed inputs, and edge cases. Graceful degradation ensures your product never breaks because of an AI service outage.

Graceful degradation Retry logic Fallback responses
6

Performance Testing and Optimization

Load testing, latency profiling, and cost optimization for every AI endpoint. We ensure AI features respond within your UX requirements and optimize model selection and caching to minimize API costs.

Load testing Latency profiling Cost optimization
7

Monitoring and Observability

Dashboards and alerts for AI feature health: response times, error rates, API costs, model accuracy, and usage patterns. Know exactly how your AI features are performing and what they cost, in real time.

Real-time dashboards Cost tracking Accuracy monitoring
8

Documentation and Team Handoff

Complete documentation covering architecture decisions, API usage, prompt engineering guidelines, and troubleshooting playbooks. We do PR reviews with your team so they understand every integration point and can extend it independently.

Architecture docs PR walkthroughs Self-service ready

How AI Integration Works

1

Codebase Review

2-3 days

Understand your architecture, identify the best integration points.

2

AI Feature Design

2-3 days

Define AI capabilities, user experience, and data flow.

3

Integration Sprint

2-3 weeks

Build, test, and integrate AI features into your codebase.

4

QA and Deployment

2-3 days

End-to-end testing, staging review, and production deployment.

Ready to add AI features to your product? Book a free 30-minute discovery call to scope your integration.

Book a Free Discovery Call

AI Integration Sprint vs. Other Approaches

You have options for adding AI to your product. Here is how they compare on the dimensions that actually matter.

Salt Technologies AI

AI Integration Sprint

$15,000

Fixed price

4 weeks

To production

AI Eng + QA + Tech Lead

Full team, not a solo freelancer

Works in your codebase

PRs, your standards, your repo

Production-ready with tests

Unit tests, integration tests, docs

Error handling and monitoring

Fallbacks, observability, cost tracking

Fixed scope, fixed price

You know the cost before work begins

You own all code and IP

No vendor lock-in, no licensing fees

AI Freelancers

Upwork / Toptal

$10-30K

Hourly billing

6-12 wks

Scope creep risk

Single person, no QA

No oversight, no team structure

~

Sometimes works in your repo

Often delivers standalone scripts

Prototype-quality code

Notebooks and scripts, not production

No error handling or monitoring

Breaks under real production load

Hourly billing, scope creep

Final cost is unpredictable

You own the code

If contract terms are clear

Build In-House

Hire AI engineers

$150K+

Annual salary

3-6 mo

Hire + ramp up

~

Must hire, onboard, manage

3-6 months before any code ships

Works in your codebase

Full-time team member

~

Quality depends on hire

No guarantee until months in

~

Monitoring varies by skill

Depends entirely on who you hire

Highest risk, highest cost

Bad hire = 6+ months wasted

You own the code

Built by your employee

Bottom line: The AI Integration Sprint gives you a structured team, fixed timeline, and production-ready code at a fraction of the cost and risk of hiring in-house. Unlike freelancers, we deliver tested, documented code that your team can maintain and extend.

AI Integration Services: Pricing and Timeline

Timeline

4 weeks

Starting At

$15,000

What Affects AI Integration Cost

  • Codebase complexity and tech stack
  • Number of AI features to integrate
  • Data preparation requirements
  • Testing and compliance requirements

Get a fixed quote for your AI integration project

Tell us about your product, tech stack, and the AI features you want to add. We scope the sprint, give you an exact price and timeline, and identify the highest-impact features to ship first.

Book a Free Consultation
Free 30-min call, no obligation Fixed price before work begins You own all code and IP No vendor lock-in

AI Integration by Industry

Every industry has different AI integration opportunities. We tailor the sprint to your domain, your data, and your compliance requirements.

AI Integration for SaaS Products

Add AI-powered search, content generation, in-app copilots, and smart recommendations to your SaaS platform. Increase user engagement and reduce churn with AI features your competitors are already shipping.

Learn more about AI for SaaS

AI Integration for Healthcare

Integrate HIPAA-compliant AI features into EHR systems, patient portals, and clinical tools. Document processing, clinical note summarization, medical coding assistance, and intelligent triage built with PHI-safe architecture.

Learn more about AI for Healthcare

AI Integration for Fintech

Add AI-powered fraud detection, risk scoring, document verification, and intelligent customer service to your financial platform. SOC2 and PCI-DSS compliant integration with full audit trails.

Learn more about AI for Fintech

AI Integration for E-commerce

Integrate AI-powered product recommendations, semantic product search, automated product descriptions, and dynamic pricing into your e-commerce platform. Boost conversion rates and average order values.

Learn more about AI for E-commerce

AI Integration Technology Stack

We select the optimal AI models, frameworks, and tools based on your product's requirements, your existing stack, and your performance, cost, and privacy constraints. Every integration is built to work with your technology, not replace it.

Your Existing Stack OpenAI GPT-4o Anthropic Claude Google Gemini LangChain RESTful APIs GraphQL Prompt Engineering Evaluation Frameworks LangSmith / Langfuse Vector Databases Python Node.js CI/CD Integration

Why Choose Salt Technologies AI for AI Integration

We are not a generic dev shop bolting on API calls. Here is what makes our AI integration services different from every other option.

We Work in Your Codebase

We follow your coding standards, use your review process, and submit PRs your team can review. No black-box deliverables or separate repositories.

Production-Ready Code With Tests

Every line of code comes with unit tests, integration tests, and documentation. We ship production-grade code, not throwaway scripts or notebooks.

Full-Stack AI Team

Your sprint includes an AI engineer, QA specialist, and tech lead. Not a solo freelancer figuring things out. A structured team with defined roles and accountability.

We Adapt to Your Stack

We work with React, Next.js, Vue, Angular, Node.js, Python, Ruby, Go, Java, AWS, Azure, GCP, and more. The "integration" part means we adapt to your technology, not the other way around.

14+

Years of Experience

800+

Projects Delivered

100+

Engineers

4.9★

Clutch Rating

AI Integration Services: Frequently Asked Questions

How much does AI integration cost?
Our AI Integration Sprint starts at $15,000. Final pricing depends on your codebase complexity, the number of AI features, and integration requirements. You get a fixed quote after the codebase review.
Will you need access to our source code?
Yes. We work directly in your repository, following your coding standards and review processes. We submit PRs for your team to review, and all code is written to your standards.
What AI features can you add to an existing product?
Common features include: smart search, content generation, document summarization, recommendation engines, automated classification, natural language interfaces, and predictive analytics. We scope the specific features during the design phase.
How is this different from hiring AI freelancers?
We bring a structured sprint process with defined scope, timeline, and deliverables. Our team includes an AI engineer, QA, and tech lead. We integrate with your existing workflow and submit production-ready code with tests and documentation.
Do you support my tech stack?
We work with all major stacks: React, Next.js, Vue, Angular (frontend); Node.js, Python, Ruby, Go, Java (backend); AWS, Azure, GCP (cloud). The "integration" part means we adapt to your stack, not the other way around.
What happens if the AI feature needs changes after delivery?
All code is in your repository with full documentation. Your team can modify and extend it independently. If you need ongoing development, our AI Managed Pod offers continuous sprint-based AI engineering.
Can you integrate AI into a legacy or messy codebase?
Yes. We have experience integrating AI into monolithic applications, legacy PHP and Java systems, and codebases with limited test coverage. During the codebase review phase, we identify the safest integration points, add necessary test coverage around the integration surface, and document everything. We design integration points that minimize risk to existing functionality.
How do you handle data privacy when accessing our codebase?
We sign NDAs before engagement. Access is limited to team members assigned to your sprint. We follow your security protocols for repository access and can work within VPN or restricted environments if required.
Can you integrate multiple AI features in one sprint?
Yes. The 4-week sprint is scoped to deliver 1-3 AI features depending on complexity. During the codebase review and design phase, we prioritize features by impact and feasibility. If you need more features than one sprint can handle, we can run consecutive sprints or transition to an AI Managed Pod for ongoing development.
What LLMs and AI models do you use for integration?
We work with all major LLM providers: OpenAI (GPT-4o, GPT-4o-mini), Anthropic (Claude 3.5 Sonnet, Claude 3 Opus), Google (Gemini), and open-source models (Llama, Mistral). We select the model based on your accuracy requirements, latency targets, cost constraints, and data privacy needs.
How do you handle AI API costs and rate limits?
We architect integrations with cost optimization from day one: model selection based on cost-to-performance ratio, intelligent caching for repeated queries, batch processing where possible, and fallback logic for rate limit scenarios. We also set up monitoring so you can track AI API costs in real time.

Choose Your Starting Point

Most clients jump straight into the AI Integration Sprint. But if you need to validate first or want ongoing development after the sprint, we have paths for that too.

Want to Validate First?

AI Readiness Audit

Not sure which AI features will deliver the highest ROI? We audit your product, data, and workflows to identify the 3-5 highest-impact AI opportunities before you commit to a sprint.

$3,000 | 1-2 weeks
Most Popular

AI Integration Sprint

Go straight to production. AI features integrated into your codebase in 4 weeks. Tested, documented, and ready to ship. Most clients with a clear use case start here.

$15,000 | 4 weeks
After Your Sprint

AI Managed Pod

Ongoing AI development: more features, optimization, new models, and continuous iteration. A dedicated AI engineering team that ships every sprint.

$12,000/mo | Ongoing

Need a quick prototype first? Our AI PoC Sprint ($8,000) builds a working prototype with your real data so you can validate AI feasibility before committing to a full integration sprint.

No obligation to continue after any step. You own every deliverable.

View All AI Services

Getting Started Is Simple

No lengthy procurement process. No upfront commitment.

1

Book a Free Call

30-minute discovery call. Walk us through your product, your tech stack, and the AI features you want to add. No sales pitch, no pressure.

2

Get a Fixed Quote

We review your codebase at a high level, scope the AI features, and give you an exact price and timeline. No hourly billing. No surprises. You approve before we start.

3

We Integrate and Ship

Work begins immediately. You see progress through PRs, demos, and daily updates. In 4 weeks, your AI features are live and your team owns everything.

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Your Competitors Are Already Shipping AI Features

Every month without AI-powered features is users lost to competitors who have them. A $15,000 integration sprint adds AI to your product in 4 weeks. Book a free 30-minute call and we will identify the highest-impact features to ship first.