AI Chatbot with AWS Bedrock on WordPress
SleekAI routes chat requests to Bedrock through an OpenAI-compatible proxy you control (LiteLLM, Bedrock Access Gateway, or a custom Lambda) so Claude 3.7, Llama 3.1, and Titan models become drop-in providers for your WordPress site. You bring the AWS account and key.
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Keep AI spend on the AWS contract you already have
AWS Bedrock gives you Claude, Llama, Mistral, and Titan models through a single AWS-native API, with billing on the same account that already runs the rest of your stack. The catch for WordPress users is that Bedrock's native protocol is sigv4-signed and model-specific, which is not what a plug-and-play chat plugin expects. So most WordPress AI plugins skip Bedrock and force a separate cloud vendor contract.
SleekAI works around that by treating any OpenAI-compatible endpoint as a first-class provider. The pattern most Bedrock customers use is to deploy a thin adapter - LiteLLM in proxy mode, the AWS Bedrock Access Gateway sample, or a tiny Lambda + API Gateway - that exposes Bedrock as /v1/chat/completions. SleekAI then talks to that adapter exactly like it would talk to OpenAI, with a base URL like https://bedrock-proxy.example.com/v1 and a bearer key your gateway mints.
The result is that the chatbot on your WordPress site is backed by anthropic.claude-3-7-sonnet-20250219-v1:0 or meta.llama3-1-70b-instruct-v1:0 in your own AWS account, in the region you chose, billed against the AWS EDP your finance team already negotiated. Conversations land in wp_sleek_ai_chats with the model ID logged for every reply, which makes Cost Explorer reconciliation a single SQL group-by.
Workflow
Wire SleekAI to Bedrock in four steps
Deploy the adapter
Mint a key
Add the provider in SleekAI
Reconcile and tune
Try it now
Ask the Bedrock demo bot
Comparison
Generic chatbot vs SleekAI for AWS Bedrock
Generic chatbot
- Only speaks OpenAI's native API, ignores Bedrock entirely
- Cannot use sigv4-authenticated AWS endpoints
- No way to swap in claude-3-7-sonnet or llama3-1-70b model IDs
- Forces an OpenAI contract on top of your AWS EDP
- Bot logs and AWS Cost Explorer never line up
SleekAI chatbot
- Works with LiteLLM, Bedrock Access Gateway, or custom Lambda proxies
- Use Claude, Llama, Mistral, or Titan model IDs as-is
- Stays inside your AWS account and chosen region
- Bills against your existing AWS EDP, no double markup
- Logs Bedrock model ID per chat for Cost Explorer reconciliation
Features
What SleekAI gives you for AWS Bedrock
Adapter-friendly
Run LiteLLM, the AWS Bedrock Access Gateway sample, or a Lambda + API Gateway in front of Bedrock. SleekAI talks to that adapter as a normal OpenAI-compatible provider with a base URL and bearer key.
Inside your AWS tenancy
Host the adapter on Lambda, Fargate, or EC2 in the same account that runs Bedrock. Prompts and conversations never leave your AWS perimeter, and IAM scopes who can talk to which model.
Mix model providers
Run a claude-3-7-sonnet bot on the docs site and a llama3-1-70b bot on the marketing site, both routed through the same Bedrock adapter. Multibot scopes each bot to a post type, role, or URL pattern.
Use cases
Where Bedrock plus SleekAI fits
AWS-native enterprises
Companies already on an AWS EDP add a chatbot without standing up a parallel Anthropic or OpenAI contract. Spend rolls up to the same account, governed by the same SCPs and budget alerts.
Region-locked workloads
Public sector, healthcare, and EU-data sites deploy Bedrock and the proxy in a specific region (us-east-1, eu-central-1, ap-southeast-2) so the chatbot honors the same residency rules as the rest of the workload.
Centralized AI governance
Platform teams that already use Bedrock Guardrails and CloudWatch for AI usage extend the same dashboards to the WordPress site instead of onboarding a separate vendor for marketing chat.
The bigger picture
Why Bedrock matters for AWS-native sites
For shops that already standardized on AWS, every new vendor relationship is a tax. A separate OpenAI or Anthropic contract means another SOC2 review, another payment method, another budget owner, and another set of credentials to rotate. Bedrock collapses that overhead by exposing Claude, Llama, Mistral, and Titan models through a single AWS-native API governed by the IAM, KMS, and CloudTrail stack the platform team already operates.
The chatbot on your marketing site can run on Claude 3.7 Sonnet through Bedrock without the legal team ever opening a new vendor file, because there is no new vendor. SleekAI completes that picture by treating any OpenAI-compatible proxy as a normal provider. A Fargate task running LiteLLM in your VPC, an AWS Bedrock Access Gateway deployment, or a small Lambda + API Gateway combo turns Bedrock into a drop-in endpoint for WordPress.
Prompts stay inside the AWS account, Cost Explorer shows exactly how much each model spent, Guardrails apply to every request, and the chatbot ends up as one more well-governed AWS workload instead of a shadow integration.
Questions
Common questions about SleekAI for AWS Bedrock
Not directly. Bedrock's native protocol is sigv4-signed and model-specific, which differs from the OpenAI chat schema SleekAI's provider engine expects. The supported pattern is an OpenAI-compatible proxy (LiteLLM, Bedrock Access Gateway, custom Lambda) that handles sigv4 on the AWS side and exposes /v1/chat/completions to SleekAI.
LiteLLM in proxy mode is the most common choice because it ships with native Bedrock support, handles model routing, and can run on a small Fargate task or even Lambda Web Adapter. AWS's official Bedrock Access Gateway sample is a great option if you want a one-click CloudFormation deploy.
Anywhere you control: Lambda + API Gateway, Fargate, ECS, EKS, or an EC2 instance. Most teams keep it in the same VPC and region as Bedrock and put it behind a private API Gateway so only WordPress (over a VPC endpoint or VPN) can reach it.
Any model your proxy is configured to expose. Common choices are anthropic.claude-3-7-sonnet-20250219-v1:0, anthropic.claude-3-5-haiku-20241022-v1:0, meta.llama3-1-70b-instruct-v1:0, and mistral.mistral-large-2407-v1:0. The exact ID goes into the SleekAI bot's model field.
Yes, as long as the proxy is hosted inside your AWS tenancy. WordPress calls the proxy URL, the proxy calls Bedrock via the AWS SDK with IAM credentials, and Bedrock returns the response. No data leaves the AWS account that owns both the proxy and the Bedrock service.
Bedrock token usage shows up on the same AWS invoice as the rest of your spend, broken down by model in Cost Explorer. SleekAI never marks up tokens or charges per request. The plugin license is a one-time fee through the SleekWP store and unrelated to inference cost.
Yes. Most adapter projects let you attach a Guardrail ID to the proxy config so every chat request that flows from SleekAI to Bedrock is filtered against your guardrail policy. Filtered responses surface in wp_sleek_ai_chats for review.
Bedrock exposes Titan and Cohere embedding models. Point SleekAI's embeddings provider at the same OpenAI-compatible proxy with a model ID like amazon.titan-embed-text-v2:0 to build a fully Bedrock-backed retrieval pipeline grounded in your WordPress content.
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