Top 10 RAG development companies

Ten RAG development companies scored on published projects, method, deployment, certification and team size, with every fact linked to its source.

Nicholas Berryman Content Lead and Market Analyst August 26, 2025 Updated October 21, 2026 14 min read

This updated list scores the top 10 RAG development companies from 0 to 4 on five public criteria: published RAG evidence, retrieval and evaluation method, deployment, certification and capacity. Accenture and IBM Consulting lead with 88 of 100. Vstorm places seventh with 69, held back by its size and by the absence of a stated security certification. Of the 10 firms, 9 have published a RAG project with a measured result, 4 name the client, 7 state on-premise deployment and none publishes a price.

This comparison scores 10 RAG development companies on what each has published about its work with retrieval-augmented generation (RAG), the technique that lets a language model answer from an organization's own documents and cite them. Each firm is scored on delivered projects, retrieval and evaluation method, deployment options, security certification and team size. Research was done on October 9, 2026, from each firm's own pages.

The global consultancies lead the table on capacity and certification. The two firms with the strongest published project record are the two smallest by stated headcount. Vstorm publishes this comparison and is one of the 10 firms. It places seventh.

RAG development companies at a glance #

Each criterion is scored from 0 to 4, and the score is the weighted total out of 100. Firms with equal scores are listed alphabetically.

Rank	Firm	Suits	Evidence (30)	Method (20)	Deployment (20)	Compliance (15)	Capacity (15)	Score
1	Accenture	Global programs that need on-premises or sovereign options	3	4	3	4	4	88
2	IBM Consulting	Regulated organizations standardizing on watsonx	3	4	3	4	4	88
3	Deloitte	Enterprises that want RAG inside a wider transformation program	3	4	3	3	4	84
4	N-iX	Enterprises that want a dedicated RAG practice and a seven-week proof of concept	3	4	3	4	3	84
5	Deviniti	Banks and regulated teams that need self-hosted models	3	3	4	2	2	73
6	Grid Dynamics	Fortune 1000 companies that want engineering scale and a published testing method	3	4	2	2	3	71
7	Vstorm	Mid-market companies that want to own the system	4	4	3	1	0	69
8	LeewayHertz	Teams that want a platform-led start on ZBrain	2	4	2	4	2	68
9	Master of Code Global	Customer-facing and healthcare assistants	3	3	3	2	1	64
10	Neurons Lab	Financial institutions building on AWS	4	4	2	0	1	64

What a RAG development partner builds #

A RAG system joins two steps, retrieval and generation. An ingest pipeline splits the source documents into chunks, and embedding models turn each chunk into a vector that is stored in a vector database. When a question arrives, semantic search finds the chunks closest in meaning, and metadata filtering narrows them by date, source or document type. A large language model then writes the answer from those chunks and cites them.

Two tinted lanes: an ingest pipeline from documents through chunking and embedding into a vector database, and an answer pipeline from question to search, access check and cited answer that reads from the same index, with a note that enterprise RAG carries access controls over from the source systems. — A RAG system is two pipelines that meet in one index.

An enterprise RAG system adds a requirement. Access controls must carry over from the source systems, so that knowledge retrieval returns only what the person asking is allowed to see. That is why this comparison scores method and deployment as well as finished projects.

How the scores were set #

Every score rests on a public source: the firm's website, its press releases or its documentation. Where a firm does not state a fact, a named third-party source is used and marked. The references at the end list every page.

Criterion	Weight	Level 4	Level 3	Level 2	Level 1
Published RAG evidence	30	Two or more RAG projects with measured results, one for a named client	One RAG project with a measured result	A RAG project with no measured result	RAG capability described, no project
Retrieval and evaluation method	20	Level 3, plus a technical guide or an in-depth project write-up	Retrieval design and evaluation method both described	One of the two described	RAG mentioned without detail
Deployment and data control	20	Level 3, plus self-hosted models and a published project deployed that way	On-premise deployment stated	Private cloud, client cloud account or hybrid stated	Public cloud only
Security and compliance	15	Three or more audited standards stated	Two audited standards stated	One audited standard stated	Compliance described, no certification
Delivery capacity	15	10,000 or more people	1,000 to 9,999 people	250 to 999 people	50 to 249 people

Level 0 means that nothing was found, or that the firm has fewer than 50 people.

Score table of ten RAG firms: 0–4 levels per criterion shown as squares, blue for published-work criteria (evidence, method, deployment, 70 points) and violet for capacity and certification (30 points), with total scores from 88 to 64 and a red line marking the 11-point gap between the top four and the rest. — The consultancies lead on capacity and certification, which carry 30 of 100 points.

The 10 firms cover three groups a buyer meets: global consultancies, mid-size engineering firms and specialists. The list is not exhaustive. A firm was included only if it has a public page that describes RAG delivery and at least one published RAG project.

The score measures what a firm publishes. It does not measure work that a firm has delivered and not described, and it says nothing about quality on a particular project. Capacity and certification carry 30 of the 100 points, so a firm with fewer than 50 people cannot score above 85.

Vstorm publishes this comparison and sells RAG development, so readers should treat it as an interested party. The previous version of this page, published in August 2025, ranked Vstorm first. This version scores Vstorm by the same published levels as every other firm and links each fact, so that a reader can re-score any row.

1. Accenture, for global programs with on-premises and sovereign options #

Accenture reported approximately 814,000 people at the end of fiscal 2026. Its RAG work runs through AI Refinery, a platform whose developer documentation covers vector search, reranking and GraphRAG, a method that retrieves from a knowledge graph built out of the source documents. For Air France-KLM, Accenture built a generative AI factory on Google Cloud in 2025. One use case pairs language generation with internal document search, and development cycles became more than 35% faster.

AI Refinery runs on on-premises infrastructure and in sovereign clouds. Accenture states ISO 27001 and ISO 27701 certification and a CSA STAR Gold certification.

Accenture suits multi-country programs with heavy security review. This research found no dedicated RAG service page, and the 35% figure describes the whole AI factory, not retrieval quality.

2. IBM Consulting, for regulated organizations standardizing on watsonx #

IBM Consulting states over 75,000 trained consultants. IBM's RAG architecture pattern maps retrieval to watsonx Discovery and generation to watsonx.ai, and it lists evaluation metrics such as relevance and coherence. The clearest published project is internal. AskIBM, an assistant built by IBM's CIO organization, reached more than 280,000 employees in January 2024 and drew on more than 30,000 documents by July 2024.

The same pattern says watsonx.ai can run as containerized services on Red Hat OpenShift in a client's own data center. IBM Cloud lists SOC 2, ISO 27001, ISO 27701 and PCI DSS, and six watsonx products received FedRAMP authorization on April 1, 2026.

IBM Consulting suits organizations that accept the watsonx stack. This research found no external client RAG project with a measured result that names IBM Consulting.

3. Deloitte, for RAG inside a wider transformation program #

Deloitte reports nearly 500,000 people worldwide. Two case studies from Deloitte India describe RAG builds. An R&D knowledge system for a manufacturer answered with over 85% accuracy across more than 110 documents. A due-diligence system for an Asian bank produced company and market reports with over 90% accuracy. Neither client is named. A Deloitte Insights article from February 2025 covers chunking, embeddings and output checks.

Through its alliance with HPE, Deloitte delivers AI workloads on-premises or in co-location. Certification sits with member firms. Deloitte Luxembourg, for example, holds ISO 27001 and ISO 22301.

Deloitte suits enterprises that want RAG delivered alongside process and organizational change. A buyer should ask the local member firm which certifications apply to the engagement.

4. N-iX, for a dedicated RAG practice and a seven-week proof of concept #

N-iX has 2,400+ technology professionals, including 200+ specialists in AI, machine learning and data, with offices in 10 countries. Its RAG service covers consulting, architecture, pipeline development, integration, optimization and agentic RAG. A proof of concept is "typically completed within seven weeks."

Published results include contract validation that runs 10 to 20 times faster and saves 2,000 hours a year, and 70% automation of recurring legal and compliance queries. N-iX published a RAG evaluation guide on March 25, 2026 that covers metrics such as recall-at-k and faithfulness.

Its own ranking states on-premise deployment and lists ISO 27001, ISO 27701, SOC 2 Type 2 and PCI DSS.

N-iX suits enterprises that want a large team and a fixed first milestone. None of its published RAG results names the client.

5. Deviniti, for banks and regulated teams that need self-hosted models #

Deviniti, founded in Wrocław, Poland, in 2004, has 330 IT experts and ISO 27001 certification. Its RAG service covers chatbots, multi-index retrieval and deployment in private infrastructure, including local data centers. Deviniti also supports the development of Bielik, an open language model.

For Crédit Agricole Bank Polska, Deviniti built an agent for claims and after-sales correspondence. It saves the customer service team 756 hours a month and classifies documents with 95% accuracy. A service page describes that agent as self-hosted and powered by the bank's internal knowledge.

Deviniti suits teams that cannot send data to an external model provider. The Crédit Agricole case study does not describe the retrieval component, and the second RAG project, a legal assistant, has no published result.

6. Grid Dynamics, for engineering scale and a published testing method #

Grid Dynamics, founded in 2006 and headquartered in San Ramon, California, reported 4,838 people on June 30, 2026. For a Fortune 500 payments company, it built an agent platform with shared RAG services, with estimated savings of $9 million to $14 million a year. An article from June 2026 documents how the firm tests its own internal knowledge assistant: a regression suite scored by an LLM judge, with an accuracy target of 0.9 or above.

The firm holds ISO 27001 certification. Its infrastructure practice describes hybrid setups that pair cloud platforms with on-premises NVIDIA DGX clusters.

Grid Dynamics suits large companies that want many engineers and a documented testing method. This research found no statement that it deploys RAG fully on a client's own servers, and its published RAG client is not named.

7. Vstorm, for mid-market companies that want to own the system #

Vstorm is an agentic AI engineering company from Wrocław, Poland, founded in 2017, with 40+ people, including 25+ AI engineers. Published RAG results include a 95.4% success rate in workflow results for Mixam, a bilingual English and Arabic agent that answers only from its own materials for ARIJ Network, and workflow generation cut from two hours to three minutes for Synera. Pydantic wrote in July 2026 that Vstorm had put more than thirty AI systems into production on Pydantic AI.

Vstorm's custom RAG development services measure recall and grounding on the client's own query set before launch, and Vstorm has published a write-up of a production retrieval pipeline. Retrieval and inference can run in a client VPC or on the client's own servers, with a self-hosted model.

Vstorm suits mid-market companies that want to own the code and run the system themselves. It states no security certification, has fewer than 50 people, and has not published a named project that runs on a client's own servers.

8. LeewayHertz, for a platform-led start on ZBrain #

LeewayHertz builds RAG systems as custom projects and on ZBrain, a platform that shares its founder and CEO. Its site states ISO 27001, ISO 42001 and SOC 2 Type II certification. For Rackspace, it built a service-desk chatbot in Microsoft Teams that uses RAG over a ServiceNow knowledge base and opens a ticket when it cannot answer. No result figures are published for that project. A long guide to advanced RAG covers hybrid search, reranking and query rewriting.

ZBrain offers private cloud, private deployment on AWS, Azure or Google Cloud, and hybrid deployment.

LeewayHertz suits teams that prefer to configure a platform before writing custom code. Its own pages do not state headcount or a head office. Keyhole Software's ranking gives about 300 employees and San Francisco.

9. Master of Code Global, for customer-facing and healthcare assistants #

Master of Code Global, founded in 2004, has 200+ professionals across the United States, Canada, Poland and Ukraine, and ISO 27001 certification. Its strongest published RAG project is a HIPAA-compliant health companion for a US digital wellness platform. The assistant retrieves from more than 2,000 clinical documents. It engaged 18,500+ patients in its first 90 days and resolved 74% of queries without human escalation.

The firm offers cloud, hybrid or on-premise deployment, a fixed-price proof of concept, and 30 days to a working proof of value.

Master of Code Global suits teams that build patient or customer assistants. The wellness client is not named, and this research found no second RAG project with a named client.

10. Neurons Lab, for financial institutions building on AWS #

Neurons Lab is based in London, with a Singapore office and 50+ AI professionals. It works mainly with financial institutions and lists HSBC and Visa among its clients. For a capital markets fintech, it built a multi-agent platform that uses a Graph-RAG approach over more than 20,000 historical deals and returns searches in under 10 seconds at the 90th percentile. For dAppForge, a coding copilot that retrieves from a knowledge graph cut development time by 50%.

Both systems run on Amazon Bedrock. The firm says its systems are "developed and deployed within your infrastructure."

Neurons Lab suits banks and fintechs already committed to AWS. Its pages state no security certification and no on-premise option.

Shortlists by need #

Enterprise RAG

For enterprise RAG, capacity and certification usually decide the shortlist. Of the 10 firms, 5 have 1,000 or more people.

Firm	People	Audited standards stated
Accenture	Approximately 814,000	ISO 27001, ISO 27701, CSA STAR Gold
Deloitte	Nearly 500,000	ISO 27001 and ISO 22301 (Deloitte Luxembourg)
IBM Consulting	Over 75,000 trained consultants	SOC 2, ISO 27001, ISO 27701, PCI DSS, FedRAMP
Grid Dynamics	4,838	ISO 27001
N-iX	2,400+	ISO 27001, ISO 27701, SOC 2 Type 2, PCI DSS

On-premise RAG

Seven firms state on-premise RAG deployment. Only Deviniti has published a named project that runs self-hosted.

Firm	What the firm states
Deviniti	Private infrastructure and local data centers; a self-hosted agent at Crédit Agricole
Accenture	AI Refinery on on-premises infrastructure; on-premises and air-gapped deployments
Deloitte	On-premises or co-location through HPE Private Cloud AI
IBM Consulting	watsonx.ai on Red Hat OpenShift in the client's data center
Master of Code Global	Cloud, hybrid or on-premise; models inside the client's internal network
N-iX	Multi-cloud, hybrid and on-premise deployments
Vstorm	Client VPC or the client's own servers, with a self-hosted model

What to ask before choosing a RAG partner #

A ranking can only show what firms make public. Four questions close the gap.

Ask for one measured result from a comparable project, and ask what it was measured on. Only 4 of the 10 firms name a client next to a figure.
Ask how retrieval quality is tested before launch and after every change to the index or the model. A firm with a working method can name the metric and the threshold.
Decide where the system must run before asking for a price. Data governance rules often settle that question, and on-premise deployment narrows this list to seven firms.
Ask which legal entity holds each certification. In a network of member firms, the certificate may belong to another country's firm.

Four question cards with ten-dot counts: 4 of 10 firms name the client next to a figure, 8 of 10 score 4 of 4 on method, 7 of 10 state on-premise deployment, 8 of 10 state at least one audited standard; a red note says none of the 10 publishes a price. — Four questions that close the gap a ranking leaves.

Some teams do not need a development partner. If the documents are few and rarely change, an off-the-shelf assistant, or a prompt that contains the documents, can be enough.

Frequently asked questions #

What are the top RAG development companies in the UK?

Neurons Lab is the only firm in this comparison with its head office in the UK, in London. N-iX has a London office, and Accenture, Deloitte and IBM have UK practices.

Are there RAG development companies that serve Germany?

None of the 10 firms is headquartered in Germany. Accenture, Deloitte and IBM have German offices. N-iX states that it serves German clients from European delivery centers, and Deviniti and Vstorm are based in Wrocław, Poland.

Who are the top RAG development companies in the USA?

Grid Dynamics is headquartered in San Ramon, California. Master of Code Global has an office in Redwood City, California, and N-iX has one in Plantation, Florida. Accenture, Deloitte and IBM also operate in the US.

Do any RAG development companies have healthcare experience?

Two published healthcare projects carry figures. Master of Code Global built a HIPAA-compliant health companion that resolved 74% of queries without human escalation. Vstorm built a guideline-executing triage system for Schmitt-Thompson Clinical Content that reached 98% accuracy on an open 50-scenario benchmark, against 44% for the raw model.

How long does a RAG implementation take, and what does it cost?

N-iX says a proof of concept is typically completed within seven weeks and a production system takes five to eight months. Master of Code Global offers 30 days to a working proof of value. None of the 10 firms publishes a price.

References #

All pages were read on October 9, 2026.