# Cogram vs OpenAI Platform

Cogram records 4,376 monthly visits with -22.3% month-over-month growth and Contact for Pricing pricing. OpenAI Platform records 234,678,639 monthly visits with -9.6% growth and Paid pricing.

| Metric | [Cogram](https://openaitools.app/tool/cogram) | [OpenAI Platform](https://openaitools.app/tool/openai) |
| :--- | :--- | :--- |
| Website URL | https://www.cogram.com | https://openai.com |
| Categories | AI Project Management, AI Meeting Assistant, AI Email Assistant, AI Report Generator | AI Models, AI API, Large Language Models (LLMs), AI Chatbot |
| Pricing Model | Contact for Pricing | Paid |
| Monthly Visits | 4,376 | 234,678,639 |
| MoM Growth Rate | -22.3% | -9.6% |
| Primary Market | United States | United States |
| Direct Visits | 1,719 | 105,101,079 |
| Review Score | 4.2 | 4.8 |
| Saved Count | 1 | 144 |
| Supported Platforms | Website | Website |

## Cogram

>Cogram was founded in 2021 and is positioned as an AI-native alternative to the decades-old, pre-AI software stack that architecture and engineering firms still rely on. Rather than bolting a chatbot onto existing tools, Cogram rebuilds core project workflows around AI: an agent that reads and answers questions about project documents, email that files and searches itself, meeting minutes and field reports that draft into your templates, and structured RFI and submittal logs.

The platform is designed to fit around a firm's existing systems. It connects to communication tools such as Microsoft Teams, Outlook, Zoom and Google Meet, and to project and ERP platforms including Procore, Autodesk Construction Cloud, Deltek and Unanet, many of which can sync project data in. Cogram emphasizes controls as much as automation: it is SOC 2 Type II certified, supports SAML 2.0 SSO and MFA, uses AES-256 at-rest and TLS 1.3 in-transit encryption, offers optional private-cloud or on-prem storage, and states that no AI models are trained on customer data.

Cogram serves architects, engineers, consultants and general or specialty contractors, with offices referenced in San Francisco, New York, London and Berlin. Accessibility matters for adoption here, so the company offers a free 14-day self-serve trial, free guided trials with customer reference calls, and free external collaborator accounts. Commercial pricing is quoted per firm after a demo.

**Pricing & Plans:** Cogram uses contact/tailored pricing: a free 14-day self-serve trial and free guided trials are available, external collaborator accounts are free, and full pricing is provided after a demo.

- **Project AI Agent:** Ask natural-language questions across project documents, contracts and correspondence, and get answers grounded in your own files rather than generic responses.
- **Email Management:** Automatically file, organize and search email across all project correspondence so nothing gets lost in personal inboxes.
- **Automated Meeting Minutes:** Capture minutes in virtual and in-person meetings and have them drafted directly into your firm's templates.
- **RFIs & Submittals:** Log and review RFIs and submittals in a fast, user-friendly workflow that syncs with Procore and other project platforms.
- **Field Reports:** Record spoken observations and photos on site, then generate field reports inside your own document templates with minimal formatting.

**Strengths:** Purpose-built for architecture, engineering and construction rather than generic project management; Automates high-friction AEC paperwork: email filing, minutes, field reports, RFI and submittal logs; AI agent answers questions grounded in your own project documents; Strong security posture: SOC 2 Type II, SAML 2.0 SSO, MFA, encryption, and no model training on customer data

**Limitations:** Pricing is quote-based and requires a demo or sales conversation, so costs are not transparent upfront; Value depends on adoption across a whole project team, so partial rollouts may underdeliver; Deepest benefits come from integrations like Procore, Deltek and Unanet, which add setup effort; Feature scope is specialized for AEC workflows, offering less fit for unrelated industries

[Profile (Markdown)](https://openaitools.app/tool/cogram.md)

## OpenAI Platform

While ChatGPT serves end users, openai.com and the OpenAI Developer Platform (developers.openai.com) provide the foundational API, SDKs, and enterprise infrastructure powering thousands of production AI applications worldwide. In late 2026, OpenAI's API catalog is anchored by the GPT-6 and GPT-6.1 model suite—all featuring a 1.05-million-token context window and up to 128K output tokens. The lineup spans GPT-6 Astra for frontier reasoning and mission-critical research, GPT-6.1 Sol for near-Astra intelligence at one-fifth the price, GPT-6.1 Terra for fast visual reasoning and computer use, and GPT-6 Luna for ultra-high-volume, low-latency tasks, alongside specialized models like `gpt-5.3-codex` and `gpt-6-astra-law`.

The OpenAI Platform has evolved well beyond basic chat completion endpoints. Through the unified `v1/responses` API, developers can orchestrate stateful multi-step agents equipped with built-in server-side tools—including live web search, vector file search, code interpreter sandboxes, and GUI computer use—without stitching together external orchestration frameworks. Every flagship model supports configurable reasoning effort (`none`, `low`, `medium`, `high`, `xhigh`, and `max`), strict JSON schema Structured Outputs, and multimodal image/audio inputs, while `gpt-live-1` powers per-second billed speech-to-speech voice agents.

OpenAI bills API usage on a transparent consumption model scaled across usage tiers (Build, Launch, and Grow, scaling up to 40M+ tokens per minute). In 2026, aggressive price cuts on the 6.x generation dropped entry-level intelligence on GPT-6 Luna to $0.10 per million input tokens and $0.50 per million output tokens, while GPT-6.1 Sol runs at $2/$10 and flagship GPT-6 Astra sits at $10/$50. Engineering teams can cut spend by 90% on repeated context using automatic Prompt Caching, save 50% on asynchronous workloads via the Batch API, and enforce regional data residency with a 10% compliance uplift.

**Pricing & Plans:** Usage-based pay-per-token API billing: GPT-6 Astra at $10/1M input and $50/1M output tokens; GPT-6.1 Sol at $2/1M input and $10/1M output; GPT-6.1 Terra at $1/1M input and $5/1M output; GPT-6 Luna at $0.10/1M input and $0.50/1M output; GPT-Live-1 voice at $0.05/minute; 90% discount on cached inputs and 50% off via Batch API.

- **GPT-6 & GPT-6.1 Model Lineup with 1.05M Context:** Spanning GPT-6 Astra ($10/$50 per MTok), GPT-6.1 Sol ($2/$10), GPT-6.1 Terra ($1/$5), and GPT-6 Luna ($0.10/$0.50), all with a 1,050,000-token context window and 128K max output.
- **Configurable Reasoning Effort Controls:** Tune thinking token budgets per API request across six granularity levels (`none`, `low`, `medium`, `high`, `xhigh`, `max`) to balance latency, accuracy, and cost.
- **Responses API & Native Computer Use Tools:** Combine model inference with hosted web search, file search, function calling, and autonomous GUI computer-use actions in a single stateful API call.
- **GPT-Live-1 Realtime Voice API:** Build ultra-low-latency multimodal voice agents billed per second ($0.05/minute) without rounding up to whole minutes.
- **90% Prompt Caching Discount & Batch API:** Cached input tokens bill at just 10% of standard input rates, while asynchronous 24-hour Batch API jobs cut both input and output token costs by 50%.

**Strengths:** 100-fold cost flexibility from GPT-6 Luna ($0.10/$0.50 per 1M tokens) up to frontier GPT-6 Astra ($10/$50 per 1M tokens); Unified 1.05M-token context window and 128K output limit across the entire flagship GPT-6 and GPT-6.1 family; 90% discount on cached input tokens and 50% Batch API discount dramatically reduce production inference bills; Industry-standard SDKs, Structured Outputs, and built-in Responses API tools minimize boilerplate agent code

**Limitations:** Long-context requests exceeding the standard window threshold trigger roughly 2x higher per-token billing rates; Flagship GPT-6 Astra ($10 input / $50 output per 1M tokens) is significantly more expensive than Claude Opus 5.5 ($4/$20) and Grok 4.7 ($2/$6); Regional data residency endpoints incur a 10% price uplift on models released after March 2026

[Profile (Markdown)](https://openaitools.app/tool/openai.md)

## Frequently Asked Questions

### How do Cogram and OpenAI Platform compare in monthly traffic?

Cogram has 4,376 monthly visits, while OpenAI Platform has 234,678,639. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Cogram has a month-over-month growth rate of -22.3%; OpenAI Platform has -9.6%.

### How does pricing compare?

Cogram: Contact for Pricing. Cogram uses contact/tailored pricing: a free 14-day self-serve trial and free guided trials are available, external collaborator accounts are free, and full pricing is provided after a demo. OpenAI Platform: Paid. Usage-based pay-per-token API billing: GPT-6 Astra at $10/1M input and $50/1M output tokens; GPT-6.1 Sol at $2/1M input and $10/1M output; GPT-6.1 Terra at $1/1M input and $5/1M output; GPT-6 Luna at $0.10/1M input and $0.50/1M output; GPT-Live-1 voice at $0.05/minute; 90% discount on cached inputs and 50% off via Batch API.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [Notion](https://openaitools.app/tool/t) | 173,441,670 | +0.1% | Freemium | The AI workspace where teams and agents get work done together | [.md](https://openaitools.app/tool/t.md) |
| 2 | [Google AI Studio](https://openaitools.app/tool/google-ai-studio) | 112,620,020 | +2% | Freemium | Provides direct API access to Google's Gemini models with generous free prototyping tiers, but lacks OpenAI's ecosystem breadth. | [.md](https://openaitools.app/tool/google-ai-studio.md) |
| 3 | [Qwen 4 (Alibaba Qwen4)](https://openaitools.app/tool/qwen-4) | 35,101,353 | -6.2% | Freemium | Alibaba Cloud's 4th-generation multimodal AI assistant and foundation model lineup (Qwen4-Max, Qwen4-Plus, Qwen4-Flash & open-weight Qwen4-27B) with 1M context. | [.md](https://openaitools.app/tool/qwen-4.md) |
| 4 | [OpenRouter](https://openaitools.app/tool/openrouter-ai) | 19,941,437 | -6.2% | Paid | Unifies hundreds of third-party models under a single API key, offering greater model choice than OpenAI's curated catalog. | [.md](https://openaitools.app/tool/openrouter-ai.md) |
| 5 | [BigModel](https://openaitools.app/tool/bigmodel) | 5,700,686 | -17% | Freemium | Provides developer APIs for Zhipu AI's proprietary GLM models, serving as an alternative enterprise foundation model stack. | [.md](https://openaitools.app/tool/bigmodel.md) |
| 6 | [fal.ai](https://openaitools.app/tool/fal-ai) | 3,093,684 | -3.7% | Paid, pay-as-you-go usage-based pricing | Optimized for lightning-fast serverless execution of generative media and image models, rather than general text LLMs. | [.md](https://openaitools.app/tool/fal-ai.md) |
| 7 | [Together AI](https://openaitools.app/tool/together-ai) | 1,645,930 | +64.9% | Freemium, Paid | Specializes in high-performance serverless inference and dedicated GPU clusters for open-source models, bypassing closed commercial restrictions. | [.md](https://openaitools.app/tool/together-ai.md) |
| 8 | [Dooray!](https://openaitools.app/tool/dooray) | 1,532,922 | -3.9% | Freemium, Free Trial, Paid, Contact for Pricing | All-in-one Korean collaboration suite for teams and public institutions | [.md](https://openaitools.app/tool/dooray.md) |
| 9 | [Replicate AI](https://openaitools.app/tool/replicate-ai) | 904,038 | -8.4% | Paid | Focuses heavily on running and fine-tuning open-source vision and language models via simple APIs, unlike OpenAI's hosted closed models. | [.md](https://openaitools.app/tool/replicate-ai.md) |
| 10 | [Atlas Cloud](https://openaitools.app/tool/atlas-cloud) | 777,031 | -16.4% | Paid | One OpenAI-compatible API for 500+ image, video, audio, and LLM models | [.md](https://openaitools.app/tool/atlas-cloud.md) |

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Source: https://openaitools.app/compare/cogram-vs-openai

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