AI Automation Services That Scale and Pay Back
Data Prism provides AI automation services for operations teams. It replaces manual work such as copying data, chasing approvals and reading documents. Solutions include RAG assistants, document processing and workflow automation built with OpenAI and AWS.
- 80%Less Manual Review Time
- 5.0Clutch Rating
- 24/7Automated Monitoring
- 3XFaster Workflow Execution
At a Glance
Less Repetitive Work - AI handles documents, approvals, data entry and reporting, so your team reviews the exceptions instead of each task by hand.
Intelligent Decision Support - Your first workflow goes live in 1 to 2 weeks, so you see results early. We then expand it to the next process.
Clear Starting Prices - Audits start at $500 and builds at $1,500. The final price depends on how many systems you connect and how clean your data is
AI Automation Services We Build
RAG-Based Knowledge Automation
RAG (retrieval-augmented generation) lets AI answer from your own documents and data, so people get current answers.
Typical uses: An internal help desk, policy and contract search, and answers for new staff.
Typical stack: OpenAI for the model, Supabase for storage and Google Cloud for hosting.
Example: An assistant that connects emails, documents and cloud storage, built with OpenAI and Supabase.AI Workflow Orchestration
We connect AI to your existing systems so requests, approvals and notifications move between them without manual hand-offs.
Typical uses: Routing leads and support tickets, approval chains, and status updates across your tools.
Typical stack: AWS Lambda and SQS for processing, with APIs and webhooks for the connections.
Example: A job platform where one action submits an application, built with serverless AWS services.Intelligent Document Processing
Intelligent document processing extracts data from invoices, contracts and emails and passes it to your ERP or CRM.
Typical uses: Invoice entry, contract review and email sorting.
Typical stack: Gemini Vision or OpenAI to read documents, with AWS S3 for storage.
Example: For Apsession, Gemini Vision reads event flyers and Instagram posts and turns them into structured records, with files stored on AWS S3.Predictive Decision Automation
AI analyzes your operational data, flags risks and unusual activity, and recommends the next action. Actions then run automatically under rules you set.
Typical uses: Alerts on unusual activity, risk scoring and next-step recommendations.
Typical stack: OpenAI for scoring and Amazon S3 for storage.
Example: A monitoring system for Maxx Source, where OpenAI scores market commentary from four finance and crypto sources.Agentic AI Automation
Through AI agent development, we build agents that read information, choose the next step and finish multi-step tasks in your tools.
Typical uses: Research tasks, follow-up drafts and questions that need several sources, such as a birthday found across contacts and calendars.
Typical stack: A language model such as OpenAI, connected to your tools and data through APIs.
Example: A personal data assistant built with OpenAI. It plans its steps, chooses from 45+ tools across email, documents, calendar and bank accounts, and combines the results into one answer.
Technologies We Use for AI-Powered Automation
Cloud Platforms
Containerization
RESTful Services
LLM & Generative AI Platforms
Workflow Automation & Orchestration
Benefits of AI Automation Consulting Services
AI Automation Resources
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Ready to find your first automation?
Book a Free Automation AuditHow Our AI Automation Services Work
Our automation consulting services begin by understanding how work moves across your business. We analyze existing tasks, systems, data flows and approval steps before moving into design, development, testing and production monitoring.
Identify opportunities
The process begins by reviewing manual tasks, system dependencies and operational bottlenecks. This helps us identify the opportunities with the strongest business impact. You receive a ranked list of the tasks worth automating and a check of whether your data is ready.
Design the Architecture
Once the gaps are identified, workflow logic, integrations, business rules and the technology stack are defined around your systems and requirements. We also agree which decisions stay with a person and set a written payback target.
Build AI Automations
Next, the automation components are built and configured to route tasks, process information and trigger actions reliably. Access controls are set at this stage.
Test with real cases
Before launch, workflows are validated using real business scenarios, test data and expected exception cases. Low-confidence results go to a person for review.
Launch, Monitor and Improve
Once approved, the solution is launched into production. We then monitor performance through logs, alerts and process metrics. As your needs change, we refine the workflows. The first 2 to 3 weeks of support are included.
Why Choose Data Prism as Your Automation Consultant?
As an AI automation agency, we build systems that run in production and can be measured. We measure each result against the process it replaces.
Business Process First Approach
Every organization has different workflows, systems and priorities. We design automations around them instead of forcing a pre-defined process into your system. Each project starts with an audit of about one week.
Diverse Team
Reliable automation depends on connected systems, trusted data and well-designed workflows. Our engineers combine AI, data engineering and cloud expertise, so the pipelines, models and deployment come from one team.
Enhance Existing Systems
We embed AI automation into your existing systems through APIs and webhooks, without disrupting established workflows. Connected systems include Shopify, ClickUp, Capsule CRM and Slack.
Focus on measurable outcomes
We record your baseline, compare results after launch and agree a written payback target, a goal rather than a guarantee. One project cut weekly prospecting from 15 to 20 hours to about 4 (High-Growth Startup Finder).
Scalable Architecture
Business needs change over time. We design automations that support new workflows and higher workloads without unnecessary redevelopment, using serverless services such as AWS Lambda and Amazon S3.
Clear limits
We do not automate rare, low-volume tasks, because the build costs more than it saves. Messy data is fixed first, because automation would repeat errors. Decisions that need legal accountability stay with a person.
Our Certifications
Engagement Models and Pricing
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Estimate Your Project CostIndustries We Serve
We have delivered AI automation projects in these industries.
Finance
AI scores market commentary from finance and crypto sources, and alerts go out as new content appears. Transcripts are pulled from video too.
Real Estate
Facebook posts become standard listing records, and communities are monitored around the clock. The listings are then prepared for review.
Recruitment
The platform finds jobs across many sources and submits applications on hiring platforms. Resumes and documents are processed too.
Marketing
Instagram and Facebook campaign data is standardized, and missing captions are recovered with OCR. Event details are pulled from flyers.
SaaS and technology
An AI assistant answers questions across email, documents, calendar, contacts and bank accounts from one workspace.
Success Stories
Real-Time Financial Sentiment Intelligence
Reviewing market commentary by hand was slow. OpenAI now scores content from 4 sources. Result: about 80% less review time.
Read the case study
Off-Market Property Intelligence
Property leads were buried in Facebook posts. OpenAI turns them into listing records. Result: fresh listings delivered 24/7.
Read the case study
AI-Powered Job Search and Application Platform
Applying across many job sites was manual and repetitive. A serverless AWS platform now submits applications for you. Result: a job inventory refreshed 24/7.
Read the case study
Influencer Marketing Analytics
Campaign data was spread across Instagram and Facebook, and teams collected it by hand. Recurring collection now standardizes it in one format. Result: reliable reporting for 3 global brands.
Read the case studyOur Clients
Frequently Asked Questions
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