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CometAPI

CometAPI

#471 most-used

Route any LLM call through one API key

ProductivityDocumentsDeveloperAIAutomation

CometAPI is an OpenAI-compatible AI gateway that gives you access to dozens of large language models — GPT-4o, GPT-4o-mini, Claude, Gemini, and more — through a single API endpoint and one credential. Connect it to Actionist and your agents can generate text, classify content, translate documents, review code, summarise data, and run structured prompts against any model your team prefers, with full control over temperature, token limits, and sampling behaviour.

Try CometAPI with ActionistVisit CometAPI
Average time saved
14 hours
per person · per month
≈ 2 workdays back

Eliminates manual work. Agents eliminate manual content drafting, document reading, data extraction from unstructured text, and report compilation by routing each task through CometAPI automatically.

Schedule

What your CometAPI agent runs on autopilot

A week of scheduled jobs your Actionist agent will execute on your behalf.

28Scheduled jobs
7Agents at work
24/7Always on
Agents
Wed–Fri
Wed
Thu
Fri
7a
8a
9a
10a
11a
12p
1p
2p
3p
4p
5p
6p
Multi-app workflows

CometAPI × every other app you use

End-to-end automations that span multiple apps — each one a real business outcome.

6Workflows
11Apps spanned
~22 hrsSaved / week
6Personas served
For support
Featured3 apps

Summarise and triage inbound support tickets

When a new ticket arrives in Zendesk, the agent sends the full message body to CometAPI for a three-sentence summary and an urgency classification. The summary and priority label are written back to the ticket as an internal note, and high-priority tickets are automatically escalated to a Slack channel so the team responds before a human even reads the raw message.

~4 hrs

Time saved for your team — every week, on autopilot

The flow
Trigger·When a new ticket arrives in the support inbox
Trigger
Step 1
Zendesk
Detect new inbound support ticket
write
Step 2
CometAPI
Summarise ticket text in three sentences
write
Step 3
CometAPI
Classify ticket urgency as low, medium, or high
write
Step 4
Zendesk
Add summary and priority label as internal note
write
Step 5
Slack
Post high-priority ticket alert to #support-escalations
Result
Summarise ticket text in three sentencesClassify ticket urgency as low, medium, or highAdd summary and priority label as internal notePost high-priority ticket alert to #support-escalations
The win
Saved per run
3 min
Runs / week
~80×
Every ticket is read and triaged before a human opens the queue
Driven byCustomer Support Agent
ROI

Savings

What your team gets back — two angles: what you stop doing manually, and what that's worth.

Without Actionist

What you do manually today

With Actionist

What your agent runs for you

  • Sales
    40 min / week
    Manual lead research and note writing

    Reps read every form submission, research the prospect's context, and manually write personalised opening lines — 10 minutes per lead, multiplied across dozens of submissions each week.

    Sales Agent
    0 min
    Agent generates personalised lines and classifies intent

    The agent sends each submission to CometAPI, classifies the intent, and generates a personalised opening line for every prospect before any rep opens the queue.

  • Marketing
    60 min / week
    Manual content creation for every campaign

    Copywriters draft subject lines, social captions, and ad headlines from scratch for every campaign — a half-day of work for each campaign launch.

    Marketing Agent
    0 min
    Agent generates first-draft copy for every campaign

    The agent sends each campaign brief to CometAPI and returns a full set of copy options for every channel in minutes, giving creators a strong starting point instead of a blank page.

  • Customer Support
    90 min / week
    Agents read every ticket before triaging

    Support agents read the full text of each inbound ticket to determine urgency and write a summary for handoff — adding 3 to 5 minutes to every ticket before work even begins.

    Customer Support Agent
    0 min
    Agent summarises and triages tickets before any human reads them

    CometAPI classifies urgency and produces a three-sentence summary for every inbound ticket so the support team opens a sorted, labelled queue and starts with context already in hand.

  • Human Resources
    50 min / week
    Manual CV screening for every application

    Recruiters read every CV in full to score it against the job description — 10 to 15 minutes per application, creating a significant bottleneck when a role receives dozens of applicants.

    Human Resources Agent
    0 min
    Agent scores and ranks every application before the recruiter opens the ATS

    CometAPI scores each CV on five criteria and writes a rationale before the recruiter reviews, so the team starts from a ranked shortlist rather than an unsorted pile.

  • Finance
    45 min / week
    Manual data entry from invoices and contracts

    Finance staff manually read each invoice or contract, identify the key fields, and type them into the tracking spreadsheet — 8 to 12 minutes per document, multiplied across all weekly receipts.

    Finance Agent
    0 min
    Agent extracts structured data from every document

    CometAPI extracts vendor name, amounts, dates, and clause text from each document and writes the results directly to the tracking spreadsheet without a human reading the document first.

  • Operations
    70 min / week
    Manual weekly report compilation

    An operations manager collects status updates from each team, reads them all, and writes a combined weekly report by hand — a process that consistently takes more than an hour each Friday.

    Operations Agent
    0 min
    Agent aggregates updates and generates the report automatically

    CometAPI receives all status updates and generates a formatted department-level report in under a minute, so the operations manager reviews rather than writes the weekly digest.

  • Legal
    60 min / week
    Manual contract review for key clauses

    Legal team members read every new contract in full to identify risk clauses and classify sensitivity — each contract takes 20 to 40 minutes of legal staff time before it is registered.

    Legal Agent
    0 min
    Agent extracts risk clauses and classifies sensitivity automatically

    CometAPI extracts indemnity, liability, and termination clauses and assigns a sensitivity classification to each new contract before any human reads it, reserving legal attention for review rather than initial triage.

+ 100s of other CometAPI automations
Average time saved
42 hrs / person / month
Calculator

Calculate what your team saves

Team size
12 people
Hourly rate
$35 / hr
Hours saved / week
42
Hours saved / year
2,100
Annual ROI
$73,500

Based on CometAPI's typical team usage — the visible tasks plus a few other automations the agent runs: ~3.5 hrs / person / week of admin work automated.

Connect

How to plug CometAPI into Actionist

Pick the connection method that suits your environment.

Connect Actionist to CometAPI using your API key. Generate a key from the CometAPI Console and paste it here — the agent authenticates every request automatically using Bearer token authentication.

1
Create a CometAPI account

Go to https://api.cometapi.com and sign up. CometAPI offers access to multiple LLMs through one account.

2
Generate an API key

Open the CometAPI Console at https://api.cometapi.com/console/token and click Generate API Key. Copy the key — you will not be able to see it again after leaving the page.

3
Paste the key into Actionist

In the Actionist Apps tab, find CometAPI, click Connect, and paste your API key into the field. Actionist will run a test call to confirm the connection is working.

Credentials you'll need
API Key*
CometAPI Console → https://api.cometapi.com/console/token → Generate API Key
Actions

14 actions your agent can call

Read and write operations available to your Actionist agent.

FAQs

Questions about CometAPI + Actionist

What is CometAPI and how does it differ from calling OpenAI directly?
CometAPI is an OpenAI-compatible API gateway that gives you access to multiple large language models — including GPT-4o, GPT-4o-mini, Claude, Gemini, and others — through a single endpoint and one API key. Instead of managing separate credentials for each AI provider, you connect once to CometAPI and choose your model per request. This is useful when you want to A/B test models, fall back to a cheaper model for high-volume tasks, or avoid vendor lock-in without rewriting your integration.
How do I connect CometAPI to Actionist?
Go to the Actionist Apps tab, search for CometAPI, and click Connect. You will be prompted for your CometAPI API key. Generate a key from the CometAPI Console at https://api.cometapi.com/console/token, paste it into the field, and click Test Connection. Actionist verifies the key with a small test call. Once confirmed, the connection is active and your agents can start using CometAPI actions.
Which language models can I use through CometAPI in Actionist?
CometAPI supports models across multiple providers including OpenAI (GPT-4o, GPT-4o-mini, GPT-3.5-turbo), Anthropic (Claude), Google (Gemini), and others depending on your CometAPI plan. You specify the model name in the Send Chat Completion action's model field. The default is gpt-4o-mini, which balances capability and cost for most automation tasks. Check https://api.cometapi.com/docs for the current list of supported models.
How do I control the quality and consistency of the AI responses?
Use the temperature parameter to control randomness. Set temperature below 0.3 for factual extraction and classification tasks where consistency matters — the model will give similar outputs for similar inputs. Set temperature above 0.7 for creative tasks like brainstorming or copy generation where variety is valuable. For structured output (JSON extraction), combine a low temperature with a system prompt that explicitly specifies the expected format. The max_tokens parameter limits response length, which helps with cost control on high-volume tasks.
Can I use CometAPI for tasks that require multi-turn context, like following up on a previous answer?
Yes. Use the Run Multi-Turn Conversation action and pass the full message history as an array of messages with role fields (system, user, assistant). Each entry in the array is part of the conversation context. Build the history by appending previous responses to the messages array before each new call. This pattern is useful for iterative document drafting, step-by-step data analysis, and conversational workflows where the model needs to remember earlier answers.
How do I get structured JSON output from CometAPI instead of plain text?
Include a system prompt that explicitly instructs the model to return only valid JSON matching a specific schema. For example: 'Return a JSON object with fields: vendor_name (string), invoice_number (string), total_amount (number), due_date (string ISO8601). Do not include any other text.' Combine this with a low temperature (0.1 to 0.2) for consistency. After the action runs, parse the returned text as JSON in your workflow. For high-volume extraction tasks, test the prompt on a representative sample to confirm the model reliably produces parseable output.
How do I manage API costs when processing large volumes of items through CometAPI?
Use the max_tokens parameter to cap response length — most classification and extraction tasks need far fewer tokens than the default 4096. Choose the cheapest model that meets your accuracy bar; gpt-4o-mini handles most triage, classification, and short-generation tasks at a fraction of the cost of gpt-4o. For batch jobs, process items sequentially rather than in parallel to stay within rate limits. Monitor your usage in the CometAPI Console at https://api.cometapi.com/console.
Does CometAPI work for languages other than English?
Yes. The underlying language models — GPT-4o, Claude, Gemini — have strong multilingual capability. For translation tasks, send the source text with a system prompt specifying the target language and any domain-specific terminology to preserve. For classification and extraction in non-English text, include a system prompt in the target language for best results. CometAPI itself is model-agnostic and passes your messages to whichever model you specify, so multilingual support depends on the model chosen rather than CometAPI itself.
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