Sold by: 2Squared LLC
Most RAG systems return a probabilistic answer where the question demands a verifiable one — and the answer usually isn't in the documents alone. This platform joins document retrieval and structured data queries through Amazon Bedrock Agents, with deterministic tooling around the model, so results can be repeated and audited.
Overview
The Problem
Enterprise data does not arrive in one shape. Some of it is documents that have to be read; the rest is records that have to be counted - and the questions worth asking usually need both. A retrieval system on its own returns a plausible passage. A warehouse on its own returns a number. Neither answers a question that requires locating the exact language, interpreting what it obligates, and then checking that against the underlying data - repeatedly, and in a form someone can audit.
What We Build
We build the platform that does both. Unstructured sources are ingested, extracted with layout awareness, chunked, embedded, and indexed for semantic and lexical retrieval. Structured sources are connected wherever they already live - a relational database, NoSQL tables, an existing warehouse - or a full ETL pipeline and data lake is built when the volume warrants one. The architecture is sized to the workload rather than to a template: the same design holds from a few million rows to a few billion, with bounded-memory processing and adaptive sizing so memory footprint and cost stay flat as volume grows.
Above both sits an agent layer that uses the language model where it is genuinely strongest - interpretation, intent, disambiguation - and defers to deterministic tooling everywhere else: exact lookups, queries issued through Action Group tools, and citations resolving to the source line. The model is a multiplier on the data layer, not a replacement for it. Results are reproducible and can be traced back to what produced them.
Example Use Case: Contract Compliance Against Spend Data
A legal or procurement team needs to determine whether supplier invoices comply with contracted terms. The platform ingests contract documents (PDFs, scanned images), extracts clauses with layout-aware parsing via Amazon Textract, and indexes them for retrieval. When a user asks whether a specific charge is permitted, the Bedrock Agent locates the relevant contract language, interprets the obligation, then queries the structured spend or invoice data through Action Group tools to verify amounts, dates, or thresholds - returning a single determination with citations that resolve to the exact contract clause and the corresponding data record.
Security and Data Handling
All infrastructure is deployed into your own AWS account. Data remains encrypted at rest (via AWS KMS) and in transit (TLS). IAM policies follow least-privilege principles. Network isolation is configured to the workload. The consultant does not retain customer data after handover - your team holds full ownership and control of the production system.
Who Delivers the Work
2 Squared LLC is an independent consultancy led by a senior architect holding both AWS Professional certifications - AWS Certified Solutions Architect - Professional and AWS Certified Generative AI Developer - Professional. Engagements are delivered directly by the practitioner who scoped them - no handoffs between sales and delivery.
AWS Services Used
Amazon Bedrock and Amazon Bedrock Agents (including Action Groups), Amazon Textract, Amazon S3, AWS Glue, Amazon Athena, Amazon Aurora PostgreSQL-Compatible Edition with pgvector, Amazon DynamoDB, Amazon RDS, AWS Step Functions, AWS Lambda, AWS Fargate, Amazon Cognito, Amazon CloudWatch, and the AWS Cloud Development Kit (AWS CDK).
Engagement Shape
Engagements follow a clear progression: discovery and architecture design, data pipeline build, agent integration and testing, then full handover. Delivery is infrastructure-as-code deployed into your own AWS account, with CI/CD, observability, and complete documentation. Scope, timeline, and pricing are confirmed by private offer following a short discovery call.
Highlights
- Answers that need both the document and the data. Most retrieval systems return a passage; most warehouses return a number. This platform locates the exact language in an unstructured source, interprets what it requires, then queries the structured data behind it through Amazon Bedrock Agents and Action Group tools — returning one determination, with citations that resolve back to the source line.
- Sized to your workload, not to a template. Structured data is connected where it already lives — relational, NoSQL, an existing warehouse — or a full ETL pipeline and data lake is built when the volume warrants one. The same architecture holds from a few million rows to a few billion, with bounded-memory processing and adaptive sizing so per-task memory and the cost curve stay flat as volume grows.
- Probabilistic where it helps, deterministic where it counts. The language model handles interpretation and intent; exact lookups, direct queries and validation run as deterministic tooling, so results are reproducible and auditable rather than merely plausible. Delivered as AWS CDK into your own AWS account with CI/CD, observability and full handover — no black boxes, no lock-in.
Details
Sold by
Categories
Delivery method
Deployed on AWS
New
Introducing multi-product solutions
You can now purchase comprehensive solutions tailored to use cases and industries.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Resources
Vendor resources
Support
Vendor support
Support Contact: mpavlovich@2squared.ai
Pre-Purchase Support
Scoping, architecture, and feasibility questions are answered directly by the AWS Certified Solutions Architect - Professional who will deliver the work. Response time: within one business day.
During Engagement
Direct email access plus scheduled calls, with working hours aligned to U.S. business hours. Decisions, architecture and progress are tracked in the shared repository, so there is no reporting layer between you and the work.
Typical engagement milestones:
- Discovery and architecture design
- Data pipeline build
- Agent integration and testing
- Full handover with documentation
After Handover
Every engagement includes a defined support and warranty period, with scope and duration agreed in the private offer before work begins. Because delivery is infrastructure-as-code deployed into your own AWS account, your team holds full control of the system and is never dependent on us to run, extend or change it.
Support is provided in English.